From 837e846ef7a2a12e81d62a9fdcc9f03dda204159 Mon Sep 17 00:00:00 2001 From: Mehrtash Babadi Date: Wed, 4 May 2016 13:29:16 -0400 Subject: [PATCH] Merge pull request #444 from broadinstitute/mb_bayesian_het_pulldown. Closes #56 and #67. * Bayesian Het pulldown tool * Updated CNV-methods.tex (reverted the accidentally deleted section) Renamed naturalLogSumExp to logSumExp everywhere Added three levels of verbosity (BASIC, INTERMEDIATE, FULL) for writing/reading AllelicCountCollection Automatic detection of verbosity mode in reading AllelicCountCollection from file Updated AllelicCount R == L comparator ("equals") to ignore extra metadata when it is not available for both R and L Refactored DataLine parsers to AllelicCount New tests for AllelicCountCollection and AllelicCount New tests in GetBayesianHetCoverageIntegrationTest Removed extra "add" methods in AllelicCountCollection in favor of just one in order to decouple from the future changes in the constructor of AllelicCount MANY small fixes from the previous round of review * New AllelicCountReader and AllelicCountWriter classes and unit tests (in AllelicCountCollectionUnitTest). Abstraction of Heterozygous priors with balanced and hetergeneous implementations and unit tests. Refactoring of unit tests. * Changed POS to POSITION in all unit test Het pulldown resource files to conform with the new AllelicCountTableColumns convention * Incorporated all suggested changes from the last PR review. Minor cosmetic changes (blank lines) here and there for conformity with the existing code. * Generalized the signature of HeterozygousPileupPriorModel#getHetLogLikelihood + minor changes from the last PR review. --- build.gradle | 2 +- docs/CNVs/CNV-methods.pdf | Bin 525353 -> 711029 bytes docs/CNVs/CNV-methods.tex | 102 +++- docs/CNVs/figs/AlleleFractionPrior1.pdf | Bin 0 -> 64645 bytes docs/CNVs/figs/AlleleFractionPrior2.pdf | Bin 0 -> 61663 bytes .../ExomeStandardArgumentDefinitions.java | 3 + .../hellbender/tools/exome/AllelicCount.java | 87 +++- .../tools/exome/AllelicCountCollection.java | 69 ++- .../tools/exome/AllelicCountReader.java | 79 ++++ .../tools/exome/AllelicCountTableColumns.java | 63 ++- .../tools/exome/AllelicCountWriter.java | 89 ++++ .../BalancedHeterozygousPileupPriorModel.java | 26 ++ .../exome/BayesianHetPulldownCalculator.java | 436 ++++++++++++++++++ .../tools/exome/GetBayesianHetCoverage.java | 310 +++++++++++++ .../tools/exome/GetHetCoverage.java | 5 +- .../tools/exome/HetPulldownCalculator.java | 5 +- ...rogeneousHeterozygousPileupPriorModel.java | 189 ++++++++ .../exome/HeterozygousPileupPriorModel.java | 53 +++ .../AlleleFractionLikelihoods.java | 2 +- .../MinorAlleleFractionCache.java | 2 +- .../utils/GATKProtectedMathUtils.java | 18 +- .../utils/hmm/ForwardBackwardAlgorithm.java | 10 +- .../exome/AllelicCountCollectionUnitTest.java | 66 ++- .../tools/exome/AllelicCountUnitTest.java | 41 ++ ...BayesianHetPulldownCalculatorUnitTest.java | 332 +++++++++++++ ...GetBayesianHetCoverageIntegrationTest.java | 292 ++++++++++++ .../exome/GetHetCoverageIntegrationTest.java | 20 +- .../exome/HetPulldownCalculatorUnitTest.java | 28 +- ...sHeterozygousPileupPriorModelUnitTest.java | 49 ++ .../utils/GATKProtectedMathUtilsTest.java | 2 +- .../hellbender/utils/hmm/TestHMModel.java | 12 +- .../tools/exome/allelic-pon-test-pon-bad.tsv | 2 +- .../exome/allelic-pon-test-pon-normal.tsv | 2 +- .../exome/allelic-pon-test-sample-bad.tsv | 2 +- .../exome/allelic-pon-test-sample-event.tsv | 2 +- .../exome/allelic-pon-test-sample-normal.tsv | 2 +- .../tools/exome/{snps.tsv => snps-basic.tsv} | 2 +- .../tools/exome/snps-for-acnv-modeller.tsv | 2 +- .../exome/snps-for-allelic-integration.tsv | 2 +- .../snps-for-small-segment-merging-base.tsv | 2 +- .../hellbender/tools/exome/snps-full.tsv | 5 + .../tools/exome/snps-intermediate.tsv | 5 + ...fied-for-allelic-fraction-segmentation.tsv | 2 +- .../exome/test_fake_generated_pileup.txt | 60 +++ 44 files changed, 2350 insertions(+), 132 deletions(-) create mode 100644 docs/CNVs/figs/AlleleFractionPrior1.pdf create mode 100644 docs/CNVs/figs/AlleleFractionPrior2.pdf create mode 100644 src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountReader.java create mode 100644 src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountWriter.java create mode 100644 src/main/java/org/broadinstitute/hellbender/tools/exome/BalancedHeterozygousPileupPriorModel.java create mode 100644 src/main/java/org/broadinstitute/hellbender/tools/exome/BayesianHetPulldownCalculator.java create mode 100644 src/main/java/org/broadinstitute/hellbender/tools/exome/GetBayesianHetCoverage.java create mode 100644 src/main/java/org/broadinstitute/hellbender/tools/exome/HeterogeneousHeterozygousPileupPriorModel.java create mode 100644 src/main/java/org/broadinstitute/hellbender/tools/exome/HeterozygousPileupPriorModel.java create mode 100644 src/test/java/org/broadinstitute/hellbender/tools/exome/BayesianHetPulldownCalculatorUnitTest.java create mode 100644 src/test/java/org/broadinstitute/hellbender/tools/exome/GetBayesianHetCoverageIntegrationTest.java create mode 100644 src/test/java/org/broadinstitute/hellbender/tools/exome/HeterogeneousHeterozygousPileupPriorModelUnitTest.java rename src/test/resources/org/broadinstitute/hellbender/tools/exome/{snps.tsv => snps-basic.tsv} (61%) create mode 100644 src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-full.tsv create mode 100644 src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-intermediate.tsv create mode 100644 src/test/resources/org/broadinstitute/hellbender/tools/exome/test_fake_generated_pileup.txt diff --git a/build.gradle b/build.gradle index 785da3157d0..261ec0a59a5 100644 --- a/build.gradle +++ b/build.gradle @@ -290,7 +290,7 @@ test { // set heap size for the test JVM(s) jvmArgs = ['-Xmx6G'] - + String CI = "$System.env.CI" maxParallelForks = CI == "true" ? 1 : 2 diff --git a/docs/CNVs/CNV-methods.pdf b/docs/CNVs/CNV-methods.pdf index b083b44c69dcc540d98fdb92e5172fee4c970e12..5532a102d06d51aa2015f61d72358854b122d816 100644 GIT binary patch delta 437047 zcmZ6RQ+t>Vpk-s*PMXHHZ5xek+j(Q#W@FoS(x^#e+cxJrbFOCY_CMJBS!-8BkUTch zCXj=&rT^f9plVQ%00l}W;r-^kcYKu5eua*FwOq;HdN;)EEq;P%j0+W&M5W;O3_6^I z`6u*`f;bfkMPd&^s}-q?-pySg5?2h+3MCWHjx+CM6R$5VMs!$!R1hl@uN~F@8WdT; z1-)GL0?}|q;GWEKmK9zBkIhZ+_2~FTezmX2XF?nzDk2g{0ScrBq`rqVm44oH3P#{R 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z9PI72RMef*7bBBrea<7K3&SoY4wE_+9Nx%%?$09=gVfw<&;aQV$=b`+HTXLg^nDY* zodjLJO!wnt@THEA8M-LyNps8u$_6EMv6>#iCHG{rQg@%`LW~`=9aC;q6!(yn=gOz5 zHoR&F-(^qXVz0xFC9B)X)nXJB- z4t~YhT|s0o;Or}-I9YeDRpfD4<6!3IE=#xK;9L{u=Y$QK8tK=iJoC*5Op>*Y)Dc58 z;`(k+gxa(`Q{?HnkIP<3rt-`lgSyr{X1iJu%#V-qakP<8O9bfp{5?bm1##oU4k|m) z^nul5mFb)4Gs|gOG_oG|^2M3nov4R3W&s@ZdQ~g&3WbIk%{4686x=$=MFAkw(f) & \qquad f^* < f \leq \frac{1}{2}, +\end{array} +\right. +\end{equation} +where: +\begin{align} +f_\mathrm{th} &= \frac{1 - \rho_\mathrm{max}}{N_c \, \rho_\mathrm{max} + 2(1-\rho_\mathrm{max})},\nonumber\\ +f^* &= \frac{1 - \rho_\mathrm{min}}{N_c \, \rho_\mathrm{min} + 2(1-\rho_\mathrm{min})},\nonumber\\ +P_<(f) &= \frac{(\rho_\mathrm{max} (f N_c-1)-1) (f ((N_c-2) \rho_\mathrm{max}+2)+\rho_\mathrm{max}-1)+2 \rho_\mathrm{max} (f (f N_c-2)+1) \log \left(\frac{\rho_\mathrm{max} (f (N_c-2)+1)}{1-2 f}\right)}{2 \, (f-1)^2 \, f^2 \, N_c^2 \, \rho_\mathrm{max} \, (\rho_\mathrm{max}-\rho_\mathrm{min})},\nonumber\\ +P_>(f) &= \frac{(\rho_\mathrm{max}-\rho_\mathrm{min}) (\rho_\mathrm{max} \rho_\mathrm{min} (f (N_c-2)+1) (f N_c-1)+2 f-1)+2 \rho_\mathrm{max} \rho_\mathrm{min} (f (f N_c-2)+1) \log \left(\frac{\rho_\mathrm{max}}{\rho_\mathrm{min}}\right)}{2 \, (f-1)^2 \, f^2 \, N_c^2 \, \rho_\mathrm{max} \, \rho_\mathrm{min} \, (\rho_\mathrm{max}-\rho_\mathrm{min})}. +\end{align} +Fig.~\ref{fig:AFprior} shows two examples of this prior along with the version with discrete copy number summations.\\ + +\begin{figure} +\center +\includegraphics[scale=0.7]{figs/AlleleFractionPrior1.pdf} +\includegraphics[scale=0.7]{figs/AlleleFractionPrior2.pdf} +\caption{Two examples of the \REF~allele fraction prior $P(f|\mathsf{Het})$ at Het sites based on minimum/maximum non-germline cells and maximum copy number. The blue lines denote the continuous approximation given in Eq.~\eqref{eq:AFpriorcont}, The discontinuous organge lines denote the result with discrete copy number summation given in Eq.~ (the delta function peak at $f=1/2$ is not shown).} +\label{fig:AFprior} +\end{figure} + +\noindent {\bf The Bayesian decision rule:} Using the Bayes' theorem, the log odds of heterozygosity is found as: +\begin{equation} +\log \mathrm{odds}(\mathsf{Het}_j) = \log\,P(\{R_{kj}\}|\mathsf{Het}_j) + \log\,P(\mathsf{Het}_j) - \log\,P(\{R_{kj}\}|\mathsf{Hom}_j) - \log\,P(\mathsf{Hom}_j). +\end{equation} +In order to evaluate the right hand side, we need to have knowledge of the prior $P(\mathsf{Het}_j)$. This can be worked out from population statistics. Otherwise, we may use the flat prior $P(\mathsf{Het}_j) = 1/2$.\\ + + +Having the log odds, the decision rule is simple: we call a \HET~site if its odds exceeds a given threshold: +\begin{equation} +\mathrm{Call}~\mathsf{Het}_j \quad \Leftrightarrow \quad \log \mathrm{odds}(\mathsf{Het}_j) > \log\frac{1 - 10^{-s_\mathsf{Het}}}{10^{-s_\mathsf{Het}}} = \log(10^{s_\mathsf{Het}}-1), +\end{equation} +where we have defined the {\em \HET~calling stringency parameter $s_\mathsf{Het}$} as a convenient parametrization of the decision boundary. Finally, we note that the log likelihoods scale linearly with the read depth $N_j$ (each read results in an additional multiplicative term). Therefore, the statistic $\log \mathrm{odds}(\mathsf{Het}_j)$ linearly deviates from the decision threshold $\log(10^{s_\mathsf{Het}}-1) \propto s_\mathsf{Het}$ as the read depth increases.\\ + +\noindent {\bf Increasing power using haplotype information:} +Todo. The basic idea is to utilize SNP correlations to test multiple correlated sites simultaneously for heterozygosity (1) to increase power, and (2) to improve the prior on $\mathsf{Ref}_j/\mathsf{Alt}_j$. A good starting point to run $\mathsf{HaplotypeCaller}$ on a few normal/tumor reads and check the strength/range/size of correlations between SNP constellations. + \section{GATK CNV/ACNV Models} \label{models} \subsection{Copy-ratio model} \label{copy-ratio-model} @@ -384,7 +482,6 @@ \subsection{Calling segments after allelic CNV workflow} \label{ACNV-caller} Once this converges, the main objects of interest are the posterior probabilities of different allele counts, $P(v_{sm} = 1, w_{sn} = 1) = \sum_k E \left[ z_{sk} v_{sm} w_{sp} \right]$. For the purposes of guessing phylogeny the fractions $\rho_k$ are also interesting. - \section{Germline Exome CNVs} \label{germline} The GATK treats germline CNVs differently from somatic CNVs. This is partly due to fundamental differences, such as the absence of subclones in the germline setting. However, many arbitrary inconsistencies are historic in nature, arising from the germline algorithm's origins in the XHMM method. It is important to keep this in mind when reading these notes. The two most significant differences between the GATK's germline and somatic workflows is are the neglect of allelic information (i.e. alt and ref read counts at het sites) in the germline workflow and the use of an HMM for simultaneous segmentation and calling in the germline workflow. @@ -447,8 +544,7 @@ \subsection{Germline HMM} \label{germline-hmm} The emission model is as follows. Each hidden state emits a normally-distributed Z-score. The means are $-M$, 0, and $+M$ for deletion, neutral, and duplication states, respectively, where $M$ is s user-specified parameter whose default is 3. Each emission distribution is given unit variance. This model is quite wrong. Consider a duplication. The tangent-normalized coverage ought be be roughly 0.5 times the proportional coverage -- the raw coverage is $3/2$ that of a diploid target, leaving $1/2$ remaining after (ideal) tangent-normalization. Then division by the target standard deviation to get a Z-score yields who-knows-what. Since different targets have different average proportional coverage, the global parameter $M$ is misguided. Basically, the current model is not a model at all, but a heuristic. - -\section{Proposed Methods} \label{proposed-methods} +\section{Proposed Methods} \label{proposed-methods} \subsection{Using Panel of Normals for Allelic Fraction Model} \label{allelic-PoN} diff --git a/docs/CNVs/figs/AlleleFractionPrior1.pdf b/docs/CNVs/figs/AlleleFractionPrior1.pdf new file mode 100644 index 0000000000000000000000000000000000000000..d10d9a67faa123a692c1e0cd667ed431ad8ff823 GIT binary patch literal 64645 zcmZs?Wl$VZ*S6cZLvV+|g1fuBySoQ>w-6+_OMu`K+}+(Bg1ZEFx0Ae9-&1v_rh3i3 zdd*(@Ui(j1ci$9BViNSs4D9d}4QG`v@T?#vkb}t=cs@Q5qnx?DrK=T)?JrV+2Z2D0 z64th^=FWekt+A`Qn7OHgnK`_G0KAKZ#{qecvhIK*qxU&kl`jD=wDYh;Wo5lUmk>B7DmVU6da#OMA0RfBszorOW(Ocvh82ahdUGd*gnV_P2TP9k?E-H!t7`vDE_g|*$ ztWS7VJ^;hoyPAuEEaDe5tv1XWJ$?1B+NFQ8=X!H-b62+C7N)85Q){JP~d=qVWk@dl6j)5Z(cTedF!0LC{(VFBwg$&)=vfPm zhvJy_B}@I8YPa2M&CWW5xb+INs$zS$8uCx{a_0B!jO*x&%GC<3Ul15{PzKaRO~olD z@yY&A!*J-YRF>N}Kl3u;j+TItBEg8obhi`62wlo?iwwLeAp~gRkq|D-pdXWYZE_l66aRxhFmprsn 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zc|ZE%y5e6H?L;|{_WeHI@u~I|%Mz9-X~E4};2bW8hJv}Et*i(lxT zs=dSI&~3}-Y;I*s46s#;-ZE8-LX%xlIwphrGykZ)qg7*XY;9!cX>62Gnk1`}R@#>$ z>rm*Y5v|^IuQW+C;&pA$;tTmfQzepMnULi#^|jm`d&){DWkhN_tH#L(r7b>)TRu5= zB<2>8RPS?mBcn@w6;2k|9zQnUKLMG^0-YJ_R*NYKtGyI%wQ^@zeZ-xVp}eMiQ`+lh z?tn|z(ZJz>Qr*4tRqvOyN=D%MpB$pIo&@UN`;{YeRx~R(GiCMFm`G=Qt=2iu`$Q`p zpN{nM58{W5Y9<_nfBNfL>?fNFgYAf#@Hp4Sa)WgnnULZ$oywugfBMzu7PhnXgX)u} zJ&#nKg*cqk+}864E}rGeQGaN>TrmZ{QZmP?WKZ!39Ick}HoanbMNnws&ZH#A4qofT zn=y?RDpqe*26x~WyD)dovUB5A;v@b=?ynnFLlUdJH2DJSc>}fr_&VP&m^lnr@!qrl z!_K12YH~2(CM9~r>X=N`9PGJ!NlTqxHkK>HCA(vY40LYxyYn*JWV39x@fc-b!H)ld z+A2sUuK0Q>r+LMDF$Hn<8!<|Q+MB79Wl^P^Mvvpd^#@(VxT;$S(S1*+LPQ2ij2&Za zit&|;cZMF!`s(Q(5ief2*gBA_z0OA|O=Mr6 z(FAC@L)5pG*ZvQw)U&!~dOBwR&r_+pslsn_htO|5?5h?S*lpiWrG8H%|1p&cg?-`2 zF_7?ft?*yTrT*tieE;oF7_+oM2KV26VlhAmSLV-YEBJ0bz}*8*XOC|V{1k5C1_hRf!&J_@k(7aWMEeWIyZCy!cqoA7 zbzRQ;`V#;?CJdk6}?L;I<1L2JDZ< z%%;b%Xj)HhIt&H_Kt>D;!vI^LlY=8*w6c-(7#0En)Iov)(n(C0vL_RO*bzbj-}Cv88I~Dyl}*B zK%fMb~b3XVZTnbwCv(@M?KkB0?{9x-6RXaE0u)2* zW==N;0tUx2?iT?Z2BvutNG6@q+>~iN1O{k($S?;Iie|=;7)D(op>PqM72LXvVk(U`*!&iN!LFhk`)AjZGw9f}4kn zFE=eho4W counts; @@ -29,25 +33,14 @@ public AllelicCountCollection() { } /** - * Constructor that reads (sequence, position, reference count, alternate count) from the specified file. - * @param inputFile file to read from + * Constructor from from file. Checks whether the input file has just the basic columns, or full columns. + * @param inputFile file to read from */ public AllelicCountCollection(final File inputFile) { Utils.nonNull(inputFile); Utils.regularReadableUserFile(inputFile); - try (final TableReader reader = TableUtils.reader(inputFile, - (columns, formatExceptionFactory) -> { - TableUtils.checkMandatoryColumns(columns, AllelicCountTableColumns.COLUMN_NAME_ARRAY, formatExceptionFactory); - // return the lambda to translate dataLines into AllelicCounts. - return (dataLine) -> { - final int position = dataLine.getInt(AllelicCountTableColumns.POSITION.toString()); - final SimpleInterval interval = new SimpleInterval(dataLine.get(AllelicCountTableColumns.CONTIG.toString()), position, position); - final int refReadCount = dataLine.getInt(AllelicCountTableColumns.REF_COUNT.toString()); - final int altReadCount = dataLine.getInt(AllelicCountTableColumns.ALT_COUNT.toString()); - return new AllelicCount(interval, refReadCount, altReadCount); - }; - })) { + try (final AllelicCountReader reader = new AllelicCountReader(inputFile)) { counts = reader.stream().collect(Collectors.toList()); } catch (final IOException | UncheckedIOException e) { throw new UserException.CouldNotReadInputFile(inputFile, e); @@ -55,13 +48,10 @@ public AllelicCountCollection(final File inputFile) { } /** - * Adds (interval, reference count, alternate count) to respective lists. - * @param interval site in 1-based format - * @param refReadCount number of reads at site matching the reference - * @param altReadCount number of reads at site different from the reference + * Adds a new {@link AllelicCount} to counts. */ - public void add(final SimpleInterval interval, final int refReadCount, final int altReadCount) { - counts.add(new AllelicCount(interval, refReadCount, altReadCount)); + public void add(final AllelicCount allelicCount) { + counts.add(Utils.nonNull(allelicCount)); } /** Returns an unmodifiable view of the list of AllelicCounts. */ @@ -70,19 +60,20 @@ public List getCounts() { } /** - * Writes out (sequence, position, reference count, alternate count) to specified file. - * @param outputFile file to write to (if it exists, it will be overwritten) + * @return a map from SimpleIntervals in counts to their integer index */ - public void write(final File outputFile) { - try (final TableWriter writer = TableUtils.writer(outputFile, - new TableColumnCollection(AllelicCountTableColumns.COLUMN_NAME_ARRAY), - //lambda for filling an initially empty DataLine - (count, dataLine) -> { - final SimpleInterval interval = count.getInterval(); - final int refReadCount = count.getRefReadCount(); - final int altReadCount = count.getAltReadCount(); - dataLine.append(interval.getContig()).append(interval.getEnd(), refReadCount, altReadCount); - })) { + public Map getSimpleIntervalToIndexMap() { + return IntStream.range(0, counts.size()).boxed() + .collect(Collectors.toMap(i -> counts.get(i).getInterval(), i -> i)); + } + + /** + * Writes out pulldown data to specified file at different verbosity levels. + * @param verbosity verbosity level + * @param outputFile file to write to (if it exists, it will be overwritten) + */ + public void write(final File outputFile, final AllelicCountTableColumns.AllelicCountTableVerbosity verbosity) { + try (final AllelicCountWriter writer = new AllelicCountWriter(outputFile, verbosity)) { writer.writeAllRecords(counts); } catch (final IOException e) { throw new UserException.CouldNotCreateOutputFile(outputFile, e); diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountReader.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountReader.java new file mode 100644 index 00000000000..27133192590 --- /dev/null +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountReader.java @@ -0,0 +1,79 @@ +package org.broadinstitute.hellbender.tools.exome; + +import com.google.common.collect.Sets; +import org.apache.commons.lang3.StringUtils; +import org.broadinstitute.hellbender.utils.Nucleotide; +import org.broadinstitute.hellbender.utils.SimpleInterval; +import org.broadinstitute.hellbender.utils.tsv.DataLine; +import org.broadinstitute.hellbender.utils.tsv.TableReader; +import org.broadinstitute.hellbender.exceptions.UserException; +import org.broadinstitute.hellbender.tools.exome.AllelicCountTableColumns.AllelicCountTableVerbosity; + +import java.io.File; +import java.io.IOException; +import java.util.HashSet; +import java.util.Set; + +/** + * Reads {@link AllelicCount} instances from a tab-separated table file. + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + */ +public class AllelicCountReader extends TableReader { + + private final AllelicCountTableVerbosity verbosity; + + /** + * Opens a reader on an a pre-existing allelic counts tab-separated file. + * + * @param file the source file where to read from. + * + * @throws IllegalArgumentException if {@code file} is {@code null}. + * @throws IOException if there is an issue trying to read the contents of the file. + * @throws RuntimeException if there is a formatting issue within the file. + * @throws UserException.BadInput if not all mandatory columns can be found. + */ + public AllelicCountReader(final File file) throws IOException { + super(file); /* the constructor of TableReader parses the header */ + + /* detect verbosity level */ + if (columns().containsAll(AllelicCountTableColumns.FULL_COLUMN_NAME_ARRAY)) { + verbosity = AllelicCountTableVerbosity.FULL; + } else if (columns().containsAll(AllelicCountTableColumns.INTERMEDIATE_COLUMN_NAME_ARRAY)) { + verbosity = AllelicCountTableVerbosity.INTERMEDIATE; + } else if (columns().containsAll(AllelicCountTableColumns.BASIC_COLUMN_NAME_ARRAY)) { + verbosity = AllelicCountTableVerbosity.BASIC; + } else { + final Set missingColumns = Sets.difference( + new HashSet<>(AllelicCountTableColumns.BASIC_COLUMN_NAME_ARRAY), new HashSet<>(columns().names())); + throw new UserException.BadInput("Bad header in AllelicCount file. Not all mandatory columns are present." + + " Missing: " + StringUtils.join(missingColumns, ", ")); + } + } + + @Override + protected AllelicCount createRecord(final DataLine dataLine) { + /* mandatory (basic) fields */ + final int position = dataLine.getInt(AllelicCountTableColumns.POSITION.name()); + final SimpleInterval interval = new SimpleInterval( + dataLine.get(AllelicCountTableColumns.CONTIG.name()), position, position); + final int refReadCount = dataLine.getInt(AllelicCountTableColumns.REF_COUNT.name()); + final int altReadCount = dataLine.getInt(AllelicCountTableColumns.ALT_COUNT.name()); + + if (verbosity == AllelicCountTableVerbosity.BASIC) { + return new AllelicCount(interval, refReadCount, altReadCount); + } else { + final Nucleotide refNucleotide = Nucleotide.valueOf(dataLine.get(AllelicCountTableColumns.REF_NUCLEOTIDE.name()).getBytes()[0]); + final Nucleotide altNucleotide = Nucleotide.valueOf(dataLine.get(AllelicCountTableColumns.ALT_NUCLEOTIDE.name()).getBytes()[0]); + final int readDepth = dataLine.getInt(AllelicCountTableColumns.READ_DEPTH.name()); + if (verbosity == AllelicCountTableVerbosity.INTERMEDIATE) { + return new AllelicCount(interval, refReadCount, altReadCount, refNucleotide, altNucleotide, readDepth); + } else { /* verbosity == AllelicCountTableVerbosity.FULL */ + final double hetLogOdds = dataLine.getDouble(AllelicCountTableColumns.HET_LOG_ODDS.name()); + return new AllelicCount(interval, refReadCount, altReadCount, refNucleotide, altNucleotide, readDepth, + hetLogOdds); + } + } + } + +} diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountTableColumns.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountTableColumns.java index 396ba964df3..8f8dba307d5 100644 --- a/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountTableColumns.java +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountTableColumns.java @@ -1,22 +1,63 @@ package org.broadinstitute.hellbender.tools.exome; -import java.util.stream.Stream; +import org.broadinstitute.hellbender.exceptions.UserException; + +import java.util.Arrays; +import java.util.Collections; +import java.util.List; +import java.util.stream.Collectors; /** - * Created by davidben on 11/30/15. + * Table columns of an allelic count tab-separated file at different verbosity levels. + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + * @author David Benjamin <davidben@broadinstitute.org> */ public enum AllelicCountTableColumns { - CONTIG("CONTIG"), POSITION("POS"), REF_COUNT("REF_COUNT"), ALT_COUNT("ALT_COUNT"); + CONTIG, + POSITION, + REF_COUNT, + ALT_COUNT, + REF_NUCLEOTIDE, + ALT_NUCLEOTIDE, + READ_DEPTH, + HET_LOG_ODDS; + + public enum AllelicCountTableVerbosity { + BASIC, INTERMEDIATE, FULL + } - private String columnName; + public static final List BASIC_COLUMN_NAME_ARRAY = createUnmodifiableList( + CONTIG, POSITION, REF_COUNT, ALT_COUNT); - AllelicCountTableColumns(String columnName) {this.columnName = columnName; } + public static final List INTERMEDIATE_COLUMN_NAME_ARRAY = createUnmodifiableList( + CONTIG, POSITION, REF_COUNT, ALT_COUNT, REF_NUCLEOTIDE, ALT_NUCLEOTIDE, READ_DEPTH); - @Override - public String toString() { - return columnName; + public static final List FULL_COLUMN_NAME_ARRAY = createUnmodifiableList( + CONTIG, POSITION, REF_COUNT, ALT_COUNT, REF_NUCLEOTIDE, ALT_NUCLEOTIDE, READ_DEPTH, HET_LOG_ODDS); + + /** + * Get {@link AllelicCount} table columns at a given {@link AllelicCountTableVerbosity} level + * + * @param verbosity verbosity level + * @return list of column names + * @throws UserException.BadInput + */ + public static List getColumns(final AllelicCountTableVerbosity verbosity) { + switch (verbosity) { + case BASIC: + return BASIC_COLUMN_NAME_ARRAY; + case INTERMEDIATE: + return INTERMEDIATE_COLUMN_NAME_ARRAY; + case FULL: + return FULL_COLUMN_NAME_ARRAY; + default: + throw new UserException.BadInput("The AllelicCount verbosity is invalid."); + } } - public static final String[] COLUMN_NAME_ARRAY = - Stream.of(values()).map(AllelicCountTableColumns::toString).toArray(String[]::new); -} \ No newline at end of file + private static List createUnmodifiableList(final AllelicCountTableColumns ... columns) { + return Collections.unmodifiableList(Arrays.asList(columns).stream() + .map(AllelicCountTableColumns::name).collect(Collectors.toList())); + } +} diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountWriter.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountWriter.java new file mode 100644 index 00000000000..c64579de791 --- /dev/null +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/AllelicCountWriter.java @@ -0,0 +1,89 @@ +package org.broadinstitute.hellbender.tools.exome; + +import org.broadinstitute.hellbender.exceptions.UserException; +import org.broadinstitute.hellbender.utils.tsv.DataLine; +import org.broadinstitute.hellbender.utils.tsv.TableColumnCollection; +import org.broadinstitute.hellbender.utils.tsv.TableWriter; +import org.broadinstitute.hellbender.tools.exome.AllelicCountTableColumns.AllelicCountTableVerbosity; + +import java.io.File; +import java.io.IOException; + +/** + * Writes {@link AllelicCount} instances to a tab-separated table file. + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + */ +public class AllelicCountWriter extends TableWriter { + + private final AllelicCountTableVerbosity verbosity; + + public AllelicCountWriter(final File file, final AllelicCountTableVerbosity verbosity) + throws IOException { + super(file, new TableColumnCollection(AllelicCountTableColumns.getColumns(verbosity))); + this.verbosity = verbosity; + } + + @Override + protected void composeLine(final AllelicCount record, final DataLine dataLine) { + switch (verbosity) { + case BASIC: + composeLineBasic(record, dataLine); + break; + case INTERMEDIATE: + composeLineIntermediate(record, dataLine); + break; + case FULL: + composeLineFull(record, dataLine); + break; + } + } + + /** + * Compose the basic-verbosity record: (contig, position, ref read count, alt read count) + * + * @param record the {@link AllelicCount} record + * @param dataLine the {@link DataLine} to the composed + */ + private static void composeLineBasic(final AllelicCount record, final DataLine dataLine) { + dataLine.append(record.getInterval().getContig()) + .append(record.getInterval().getEnd()) + .append(record.getRefReadCount()) + .append(record.getAltReadCount()); + } + + /** + * Compose the intermediate-verbosity record: (contig, position, ref read count, alt read count, + * ref nucleotide, alt nucleotide, read depth) + * + * @param record the {@link AllelicCount} record + * @param dataLine the {@link DataLine} to the composed + */ + private static void composeLineIntermediate(final AllelicCount record, final DataLine dataLine) { + dataLine.append(record.getInterval().getContig()) + .append(record.getInterval().getEnd()) + .append(record.getRefReadCount()) + .append(record.getAltReadCount()) + .append(record.getRefNucleotide().name()) + .append(record.getAltNucleotide().name()) + .append(record.getReadDepth()); + } + + /** + * Compose the full-verbosity record: (contig, position, ref read count, alt read count, + * ref nucleotide, alt nucleotide, read depth, heterozygosity log odds) + * + * @param record the {@link AllelicCount} record + * @param dataLine the {@link DataLine} to the composed + */ + private static void composeLineFull(final AllelicCount record, final DataLine dataLine) { + dataLine.append(record.getInterval().getContig()) + .append(record.getInterval().getEnd()) + .append(record.getRefReadCount()) + .append(record.getAltReadCount()) + .append(record.getRefNucleotide().name()) + .append(record.getAltNucleotide().name()) + .append(record.getReadDepth()) + .append(String.format("%.4f", record.getHetLogOdds())); + } +} diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/BalancedHeterozygousPileupPriorModel.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/BalancedHeterozygousPileupPriorModel.java new file mode 100644 index 00000000000..e4df45a730f --- /dev/null +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/BalancedHeterozygousPileupPriorModel.java @@ -0,0 +1,26 @@ +package org.broadinstitute.hellbender.tools.exome; + +import org.apache.commons.lang3.tuple.Pair; + +import java.util.Collection; + +/** + * Balanced model prior for heterozygous pileups, i.e. allele fraction = 1/2. + * + * This prior is suitable for detecting heterozygous sites when the ref to alt allele ratio is expected to be 1/2, + * which is the case for sequenced reads from pure germline samples. + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + */ +public final class BalancedHeterozygousPileupPriorModel extends HeterozygousPileupPriorModel { + + /** + * Calculates the log likelihood of heterozygosity assuming allele fraction = 1/2 + * @param coeffs list of (alpha, beta) tuples + * @return any double value + */ + @Override + public double getHetLogLikelihood(final Collection> coeffs) { + return getHetLogLikelihoodFixedAlleleFraction(0.5, coeffs); + } +} diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/BayesianHetPulldownCalculator.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/BayesianHetPulldownCalculator.java new file mode 100644 index 00000000000..191b42ab7b8 --- /dev/null +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/BayesianHetPulldownCalculator.java @@ -0,0 +1,436 @@ +package org.broadinstitute.hellbender.tools.exome; + +import com.google.cloud.dataflow.sdk.repackaged.com.google.common.collect.Sets; +import com.google.common.annotations.VisibleForTesting; +import htsjdk.samtools.*; +import htsjdk.samtools.filter.DuplicateReadFilter; +import htsjdk.samtools.filter.NotPrimaryAlignmentFilter; +import htsjdk.samtools.filter.SamRecordFilter; +import htsjdk.samtools.reference.ReferenceSequenceFileWalker; +import htsjdk.samtools.util.IntervalList; +import htsjdk.samtools.util.SamLocusIterator; +import org.apache.commons.lang3.tuple.ImmutablePair; +import org.apache.commons.math3.util.FastMath; +import org.apache.logging.log4j.LogManager; +import org.apache.logging.log4j.Logger; +import org.broadinstitute.hellbender.exceptions.GATKException; +import org.broadinstitute.hellbender.exceptions.UserException; +import org.broadinstitute.hellbender.utils.*; +import org.broadinstitute.hellbender.utils.param.ParamUtils; + +import java.io.File; +import java.io.IOException; +import java.util.*; +import java.util.stream.Collectors; + +/** + * A Bayesian heterozygous SNP pulldown calculator. Base qualities are taken into account + * to increase precision (see CNV-methods.pdf for details). + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + * @author Samuel Lee <slee@broadinstitute.org> + */ + +public final class BayesianHetPulldownCalculator { + + private final Logger logger = LogManager.getLogger(BayesianHetPulldownCalculator.class); + + /** + * A simple class to handle base read and mapping error probabilitites + */ + @VisibleForTesting + static final class BaseQuality { + private final double readErrorProbability, mappingErrorProbability; + + BaseQuality(final double readErrorProbability, final double mappingErrorProbability) { + this.readErrorProbability = readErrorProbability; + this.mappingErrorProbability = mappingErrorProbability; + } + + double getReadErrorProbability() { return readErrorProbability; } + double getMappingErrorProbability() { return mappingErrorProbability; } + } + + private final HeterozygousPileupPriorModel hetPrior; + + private static final Nucleotide[] BASES = {Nucleotide.A, Nucleotide.C, Nucleotide.T, Nucleotide.G}; + + private final File refFile; + private final IntervalList snpIntervals; + + private final int readDepthThreshold; + private final int minMappingQuality; + private final int minBaseQuality; + private final ValidationStringency validationStringency; + + /* experimental */ + private final double errorProbabilityAdjustmentFactor; + + /* interval threshold for indexing for SamLocusIterator */ + private static final int MAX_INTERVALS_FOR_INDEX = 25000; + + /* default priors */ + private static final double DEFAULT_PRIOR_REF_HOM = 0.5; /* a homozygous site being the ref allele */ + private static final double DEFAULT_PRIOR_HET = 0.5; /* a site being heterozygous */ + + /* approximate number of status updates printed to log */ + private static final int NUMBER_OF_SITES_PER_LOGGED_STATUS_UPDATE = 10000; + + /** + * Constructor of {@link BayesianHetPulldownCalculator} object + * + * @param refFile the reference genome file + * @param snpIntervals {@link IntervalList} of common SNPs + * @param minMappingQuality minimum phred mapping quality + * @param minBaseQuality minimum phred base quality + * @param readDepthThreshold minimum read depth + * @param validationStringency validation stringency + * @param errorProbabilityAdjustmentFactor (experimental) multiplicative factor for read and mapping error + * probabilities + * @param hetPrior the prior model for heterzygous pileups + */ + public BayesianHetPulldownCalculator(final File refFile, final IntervalList snpIntervals, + final int minMappingQuality, final int minBaseQuality, + final int readDepthThreshold, final ValidationStringency validationStringency, + final double errorProbabilityAdjustmentFactor, + final HeterozygousPileupPriorModel hetPrior) { + ParamUtils.isPositiveOrZero(minMappingQuality, "Minimum mapping quality must be nonnegative."); + ParamUtils.isPositiveOrZero(minBaseQuality, "Minimum base quality must be nonnegative."); + + this.refFile = Utils.nonNull(refFile); + this.snpIntervals = Utils.nonNull(snpIntervals); + this.minMappingQuality = ParamUtils.isPositive(minMappingQuality, "Minimum mapping quality must be a positive integer"); + this.minBaseQuality = ParamUtils.isPositive(minBaseQuality, "Minimum base quality must be a positive integer"); + this.readDepthThreshold = ParamUtils.isPositive(readDepthThreshold, "Read depth threshold must be a positive integer"); + this.validationStringency = Utils.nonNull(validationStringency); + this.errorProbabilityAdjustmentFactor = ParamUtils.isPositive(errorProbabilityAdjustmentFactor, + "Error adjustment factor must be positive."); + this.hetPrior = Utils.nonNull(hetPrior); + } + + /** + * Calculate the log likelihood of a read pileup is composed of a single nucelotide {@code expectedNucleotide} + * @param baseQualities map of bases to list of their calling error probabilities + * @param expectedNucleotide the expected nucleotide + * @return the log likelihood + */ + private double getSingletonLogLikelihood(final Map> baseQualities, + final Nucleotide expectedNucleotide) { + return baseQualities.get(expectedNucleotide).stream() + .mapToDouble(bq -> FastMath.log(1 - bq.getReadErrorProbability() - + 3 * bq.getMappingErrorProbability() / 4)).sum() + + baseQualities.keySet().stream() + .filter(nucl -> nucl != expectedNucleotide) + .map(baseQualities::get).mapToDouble(bqlist -> bqlist.stream() + .mapToDouble(bq -> FastMath.log(bq.getReadErrorProbability() / 3 + + bq.getMappingErrorProbability() / 4)).sum()).sum(); + } + + /** + * Calculate the log likelihood of a SNP site being homozygous for a given read pileup + * (see CNV-method.pdf for details) + * @param baseQualities map of bases to list of their calling error probabilities at the SNP site + * @param refNucleotide the ref allele nucleotide + * @param altNucleotide the alt allele nucleotide + * @param homRefPrior the prior probability of the ref allele given that the site is homozygous + * @return the log likelihood + */ + @VisibleForTesting + double getHomLogLikelihood(final Map> baseQualities, + final Nucleotide refNucleotide, final Nucleotide altNucleotide, + final double homRefPrior) { + /* return the sum of |hom,ref) and |hom,alt) likelihoods */ + return GATKProtectedMathUtils.logSumExp( + FastMath.log(homRefPrior) + getSingletonLogLikelihood(baseQualities, refNucleotide), + FastMath.log(1 - homRefPrior) + getSingletonLogLikelihood(baseQualities, altNucleotide)); + } + + /** + * Calculate the log likelihood of a SNP site being heterozygous for a given read pileup + * (see CNV-method.pdf for details) + * + * @param baseQualities map of bases to list of their calling error probabilities at the SNP site + * @param refNucleotide the ref allele nucleotide + * @param altNucleotide the alt allele nucleotide + * @return the log likelihood + */ + @VisibleForTesting + double getHetLogLikelihood(final Map> baseQualities, + final Nucleotide refNucleotide, final Nucleotide altNucleotide) { + /* non-Ref-Alt entries */ + final double errorLogLikelihood = Sets.difference(baseQualities.keySet(), + new HashSet<>(Arrays.asList(refNucleotide, altNucleotide))).stream() + .map(baseQualities::get).mapToDouble(bqlist -> bqlist.stream() + .mapToDouble(bq -> FastMath.log(bq.getReadErrorProbability() / 3 + + bq.getMappingErrorProbability() / 4)) + .sum()) + .sum(); + + final List> coeffs = new ArrayList<>(); + + /* Ref entries in the pile up */ + baseQualities.get(refNucleotide).stream().forEach(bq ->coeffs.add(new ImmutablePair<>( + bq.getReadErrorProbability() / 3 + bq.getMappingErrorProbability() / 4, + 1 - 4 * bq.getReadErrorProbability() / 3 - bq.getMappingErrorProbability() / 4))); + + /* Alt entries in the pile up */ + baseQualities.get(altNucleotide).stream().forEach(bq -> coeffs.add(new ImmutablePair<>( + 1 - bq.getReadErrorProbability() - 3 * bq.getMappingErrorProbability() / 4, + -1 + 4 * bq.getReadErrorProbability() / 3 + bq.getMappingErrorProbability()))); + + return hetPrior.getHetLogLikelihood(coeffs) + errorLogLikelihood; + } + + /** + * Returns map of base-pair to error probabilities at a given locus. All reads are considered (not just ACTG) + * @param locus locus + * @return map of base-pair to error probabilities + */ + private Map> getPileupBaseQualities(final SamLocusIterator.LocusInfo locus) { + final Map> baseQualities = locus.getRecordAndPositions().stream() + .map(rp -> new ImmutablePair<>( + Nucleotide.valueOf(rp.getReadBase()), + new BaseQuality( + errorProbabilityAdjustmentFactor * QualityUtils.qualToErrorProb(rp.getBaseQuality()), + errorProbabilityAdjustmentFactor * QualityUtils.qualToErrorProb(rp.getRecord().getMappingQuality()) + ) + )).collect(Collectors.groupingBy( + ImmutablePair::getLeft, + Collectors.mapping(ImmutablePair::getRight, Collectors.toList())) + ); + + /* make sure that the main bases {A, C, T, G} are included in the map */ + for (final Nucleotide base : BASES) { + if (!baseQualities.containsKey(base)) { + baseQualities.put(base, new ArrayList<>()); + } + } + + return baseQualities; + } + + /** + * Returns base-pair counts at a given locus. + * @param locus locus + * @return base-pair counts + */ + private static Nucleotide.Counter getPileupBaseCounts(final SamLocusIterator.LocusInfo locus) { + final Nucleotide.Counter result = new Nucleotide.Counter(); + for (final SamLocusIterator.RecordAndOffset rec : locus.getRecordAndPositions()) { + result.add(rec.getReadBase()); + } + return result; + } + + /** + * Infer the alt allele base from the pileup: we pick the base with the highest frequency that is not Ref as Alt. + * This is the maximum likelihood estimation.
+ * + * Remark: While this is definitely not the perfect way to do it and it is desirable to have both Ref/Alt + * allele information, it has no serious pitfalls either:

+ *

+ * + * @param baseQualities map from bases to error probabilities + * @param refBase the ref allele base + * @return the likely alt allele + */ + @VisibleForTesting + static Nucleotide inferAltFromPileup(final Map> baseQualities, + final Nucleotide refBase) { + /* sort the bases in the descending order by their frequency */ + final Nucleotide[] bases = BASES.clone(); + Arrays.sort(bases, (L, R) -> Integer.compare(baseQualities.get(R).size(), baseQualities.get(L).size())); + /* pick the base with highest frequency, skip over ref */ + for (Nucleotide base : bases) { + if (base != refBase) { + return base; + } + } + + /* we shouldn't be here unless the baseErrorProbabilities is malformed */ + throw new GATKException.ShouldNeverReachHereException("The Alt base can not be inferred from the " + + "pileup. The size of the pileup is: " + baseQualities.size()); + } + + /** + * Returns a {@link SamLocusIterator} object for a given {@link SamReader} and {@link IntervalList} with filters + * on minimum base quality and minimum mapping quality + * + * @param samReader a SamReader object + * @return a SamLocusIterator object + */ + private SamLocusIterator getSamLocusIteratorWithDefaultFilters(final SamReader samReader) { + final SamLocusIterator locusIterator = new SamLocusIterator(samReader, snpIntervals, + snpIntervals.size() < MAX_INTERVALS_FOR_INDEX); + + /* set read and locus filters */ + final List samFilters = Arrays.asList(new NotPrimaryAlignmentFilter(), + new DuplicateReadFilter()); + locusIterator.setSamFilters(samFilters); + locusIterator.setEmitUncoveredLoci(false); + locusIterator.setIncludeNonPfReads(false); + locusIterator.setMappingQualityScoreCutoff(minMappingQuality); + locusIterator.setQualityScoreCutoff(minBaseQuality); + + return locusIterator; + } + + /** + * For a given normal or tumor BAM file, walks through the list of common SNPs, + * {@link BayesianHetPulldownCalculator#snpIntervals}), detects heterozygous sites, and returns + * a {@link Pulldown} containing detailed information on the called heterozygous SNP sites. + * + * The {@code hetCallingStrigency} parameters sets the threshold posterior for calling a Het SNP site: + * + * hetPosteriorThreshold = 1 - 10^{-hetCallingStringency} + * hetThresholdLogOdds = log(hetPosteriorThreshold/(1-hetPosteriorThreshold)) + * = log(10^{hetCallingStringency} - 1) + * + * (see CNV-methods.pdf for details) + * + * @param bamFile sorted BAM file for sample + * @param hetCallingStringency strigency for calling a Het site + * @return Pulldown of heterozygous SNP sites in 1-based format + */ + @VisibleForTesting + Pulldown getHetPulldown(final File bamFile, final double hetCallingStringency) { + /* log odds from stringency */ + final double hetThresholdLogOdds = FastMath.log(FastMath.pow(10, hetCallingStringency) - 1); + + try (final SamReader bamReader = SamReaderFactory.makeDefault().validationStringency(validationStringency) + .referenceSequence(refFile).open(bamFile); + final ReferenceSequenceFileWalker refWalker = new ReferenceSequenceFileWalker(this.refFile)) { + if (bamReader.getFileHeader().getSortOrder() != SAMFileHeader.SortOrder.coordinate) { + throw new UserException.BadInput("BAM file " + bamFile.toString() + " must be coordinate sorted."); + } + + final Pulldown hetPulldown = new Pulldown(bamReader.getFileHeader()); + final SamLocusIterator locusIterator = getSamLocusIteratorWithDefaultFilters(bamReader); + + final int totalNumberOfSNPs = snpIntervals.size(); + logger.info("Examining " + totalNumberOfSNPs + " sites in total..."); + int locusCount = 0; + for (final SamLocusIterator.LocusInfo locus : locusIterator) { + if (locusCount % NUMBER_OF_SITES_PER_LOGGED_STATUS_UPDATE == 0) { + logger.info("Examined " + locusCount + " covered sites."); + } + locusCount++; + + final int totalReadCount = locus.getRecordAndPositions().size(); + if (totalReadCount <= readDepthThreshold) { + continue; + } + + final Map> baseQualities = getPileupBaseQualities(locus); + final Nucleotide refBase = Nucleotide.valueOf(refWalker.get(locus.getSequenceIndex()) + .getBases()[locus.getPosition() - 1]); + final Nucleotide altBase = inferAltFromPileup(baseQualities, refBase); + + /* calculate Het log odds */ + final double hetLogLikelihood = getHetLogLikelihood(baseQualities, refBase, altBase); + final double homLogLikelihood = getHomLogLikelihood(baseQualities, refBase, altBase, + DEFAULT_PRIOR_REF_HOM); + final double hetLogOdds = (hetLogLikelihood + FastMath.log(DEFAULT_PRIOR_HET)) - + (homLogLikelihood + FastMath.log(1 - DEFAULT_PRIOR_HET)); + + if (hetLogOdds > hetThresholdLogOdds) { + hetPulldown.add(new AllelicCount( + new SimpleInterval(locus.getSequenceName(), locus.getPosition(), locus.getPosition()), + baseQualities.get(refBase).size(), baseQualities.get(altBase).size(), + refBase, altBase, totalReadCount, hetLogOdds)); + } + } + + logger.info(locusCount + " covered sites out of " + totalNumberOfSNPs + " total sites were examined."); + + return hetPulldown; + + } catch (final IOException | SAMFormatException e) { + throw new UserException(e.getMessage()); + } + } + + /** + * Calculates the Het pulldown from a tumor file, given the tumor BAM file and the pulldown from a matched + * normal BAM file. + * + * Note: this method does not perform any statistical inference. The Het SNP sites are directly carried over + * from the matched normal pulldown. Here, we only collect statistics (ref count, alt count, read depth) and + * save to a pulldown. The verbosity level of the pulldown is INTERMEDIATE (see {@link AllelicCountTableColumns}). + * + * @param tumorBamFile the tumor BAM file + * @param normalHetPulldown the matched normal Het pulldown + * @return tumor Het pulldown + */ + @VisibleForTesting + Pulldown getTumorHetPulldownFromNormalPulldown(final File tumorBamFile, final Pulldown normalHetPulldown) { + try (final SamReader bamReader = SamReaderFactory.makeDefault().validationStringency(validationStringency) + .referenceSequence(refFile).open(tumorBamFile)) { + if (bamReader.getFileHeader().getSortOrder() != SAMFileHeader.SortOrder.coordinate) { + throw new UserException.BadInput("BAM file " + tumorBamFile.toString() + " must be coordinate sorted."); + } + + final Pulldown tumorHetPulldown = new Pulldown(bamReader.getFileHeader()); + final SamLocusIterator locusIterator = getSamLocusIteratorWithDefaultFilters(bamReader); + + /* get a map of SimpleIntervals in the pulldown to their index */ + final Map normalPulldownIndexMap = normalHetPulldown.getSimpleIntervalToIndexMap(); + + final int totalNumberOfSNPs = snpIntervals.size(); + logger.info("Examining " + totalNumberOfSNPs + " sites in total..."); + int locusCount = 0; + for (final SamLocusIterator.LocusInfo locus : locusIterator) { + if (locusCount % NUMBER_OF_SITES_PER_LOGGED_STATUS_UPDATE == 0) { + logger.info("Examined " + locusCount + " covered sites."); + } + locusCount++; + + final int totalReadCount = locus.getRecordAndPositions().size(); + if (totalReadCount <= readDepthThreshold) { + continue; + } + + /* find the AllelicCount from the normal pulldown */ + int indexInNormalPulldown; + try { + indexInNormalPulldown = normalPulldownIndexMap.get( + new SimpleInterval(locus.getSequenceName(), locus.getPosition(), locus.getPosition())); + } catch (NullPointerException e) { + throw new GATKException.ShouldNeverReachHereException("Can not find the required AllelicCount " + + "object in the normal pulldown. Stopping."); + } + + /* just count the alt and ref nucleotide and add to the tumor pulldown */ + final Nucleotide.Counter baseCounts = getPileupBaseCounts(locus); + tumorHetPulldown.add(new AllelicCount( + new SimpleInterval(locus.getSequenceName(), locus.getPosition(), locus.getPosition()), + (int) baseCounts.get(normalHetPulldown.getCounts().get(indexInNormalPulldown).getRefNucleotide()), + (int) baseCounts.get(normalHetPulldown.getCounts().get(indexInNormalPulldown).getAltNucleotide()), + normalHetPulldown.getCounts().get(indexInNormalPulldown).getRefNucleotide(), + normalHetPulldown.getCounts().get(indexInNormalPulldown).getAltNucleotide(), + totalReadCount) + ); + } + + logger.info(locusCount + " covered sites out of " + totalNumberOfSNPs + " total sites were examined."); + + return tumorHetPulldown; + + } catch (final IOException | SAMFormatException e) { + throw new UserException(e.getMessage()); + } + } +} diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/GetBayesianHetCoverage.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/GetBayesianHetCoverage.java new file mode 100644 index 00000000000..0642762d76b --- /dev/null +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/GetBayesianHetCoverage.java @@ -0,0 +1,310 @@ +package org.broadinstitute.hellbender.tools.exome; + +import htsjdk.samtools.ValidationStringency; +import htsjdk.samtools.util.IntervalList; +import org.apache.logging.log4j.LogManager; +import org.apache.logging.log4j.Logger; +import org.broadinstitute.hellbender.cmdline.*; +import org.broadinstitute.hellbender.cmdline.argumentcollections.ReferenceInputArgumentCollection; +import org.broadinstitute.hellbender.cmdline.argumentcollections.RequiredReferenceInputArgumentCollection; +import org.broadinstitute.hellbender.cmdline.programgroups.CopyNumberProgramGroup; +import org.broadinstitute.hellbender.exceptions.GATKException; +import org.broadinstitute.hellbender.exceptions.UserException; +import org.broadinstitute.hellbender.utils.read.ReadConstants; + +import java.io.File; + +/** + * Calls heterozygous sites and outputs information about the called sites. + * + * The tool has three modes. The mode is automatically selected based on the provided arguments: + * + *
+ *
NORMAL_ONLY
This mode is chosen if just the normal BAM file is provided. The balanced prior + * is used for estimating the likelihood of het sites (see {@link BalancedHeterozygousPileupPriorModel}).
+ * + *
TUMOR_ONLY
This mode is chosen if just the tumor BAM file is provided. The heterogeneous prior + * is used for estimating the likelihood of het sites (see {@link HeterogeneousHeterozygousPileupPriorModel}).
+ * + *
MATCHED_NORMAL_TUMOR
This mode is chosen if both normal and tumor BAM files are provided. + * The balanced prior (see {@link BalancedHeterozygousPileupPriorModel}) is used to estimate the likelihood of + * Het sites on the normal reads. The base counts on the same het sites are collected and reported from the + * tumor reads.
+ *
+ ** + * @author Mehrtash Babadi <mehrtash@brgoadinstitute.org> + */ +@CommandLineProgramProperties( + summary = "Calls heterozygous sites and output the reference and alternate base counts at the called sites. A list" + + " of SNP sites must be provided. If only the normal BAM file is provided, the job will be run in the NORMAL_ONLY" + + " mode. The output will be detailed (genomic position of het sites, alt and ref counts and nucleotides," + + " read depth, and log odds of heterzygosity). If only the tumor BAM file is provided, the job will be run in" + + " the TUMOR_ONLY mode. The output will be detailed. If both the normal and tumor BAM files are provided, the" + + " Het sites are inferred from the normal reads and the counts on the same sites will be collected from the" + + " tumor reads. The output for the normal reads will be detailed. The outout for the tumor reads will not" + + " include the log odds of heterozygosity since the inference is made from the normal reads.", + oneLineSummary = "Calls heterozygous sites and outputs information about the called sites.", + programGroup = CopyNumberProgramGroup.class +) +public final class GetBayesianHetCoverage extends CommandLineProgram { + + private final Logger logger = LogManager.getLogger(GetBayesianHetCoverage.class); + + protected static final String READ_DEPTH_THRESHOLD_FULL_NAME = "readDepthThreshold"; + protected static final String READ_DEPTH_THRESHOLD_SHORT_NAME = "readThresh"; + + protected static final String MINIMUM_MAPPING_QUALITY_FULL_NAME = "minimumMappingQuality"; + protected static final String MINIMUM_MAPPING_QUALITY_SHORT_NAME = "minMQ"; + + protected static final String MINIMUM_BASE_QUALITY_FULL_NAME = "minimumBaseQuality"; + protected static final String MINIMUM_BASE_QUALITY_SHORT_NAME = "minBQ"; + + protected static final String HET_CALLING_STRINGENCY_FULL_NAME = "hetCallingStringency"; + protected static final String HET_CALLING_STRINGENCY_SHORT_NAME = "hetS"; + + protected static final String QUADRATURE_ORDER_FULL_NAME = "quadratureOrder"; + protected static final String QUADRATURE_ORDER_SHORT_NAME = "quad"; + + protected static final String MINIMUM_ABNORMAL_FRACTION_FULL_NAME = "minimumAbnormalFraction"; + protected static final String MINIMUM_ABNORMAL_FRACTION_SHORT_NAME = "minAF"; + + protected static final String MAXIMUM_ABNORMAL_FRACTION_FULL_NAME = "maximumAbnormalFraction"; + protected static final String MAXIMUM_ABNORMAL_FRACTION_SHORT_NAME = "maxAF"; + + protected static final String MAXIMUM_COPY_NUMBER_FULL_NAME = "maximumCopyNumber"; + protected static final String MAXIMUM_COPY_NUMBER_SHORT_NAME = "maxCN"; + + protected static final String ERROR_PROBABILITY_ADJUSTMENT_FACTOR_FULL_NAME = "errorAdjustmentFactor"; + protected static final String ERROR_PROBABILITY_ADJUSTMENT_FACTOR_SHORT_NAME = "errFact"; + + @ArgumentCollection + protected static final ReferenceInputArgumentCollection REFERENCE_ARGUMENTS = + new RequiredReferenceInputArgumentCollection(); + + @Argument( + doc = "Normal BAM file (for normal-only and paired normal-tumor cases).", + fullName = ExomeStandardArgumentDefinitions.NORMAL_BAM_FILE_LONG_NAME, + shortName = ExomeStandardArgumentDefinitions.NORMAL_BAM_FILE_SHORT_NAME, + optional = true + ) + protected File normalBamFile; + + @Argument( + doc = "Tumor BAM file (for tumor-only and paired normal-tumor cases).", + fullName = ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_LONG_NAME, + shortName = ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, + optional = true + ) + protected File tumorBamFile; + + @Argument( + doc = "IntervalList file of common SNPs.", + fullName = ExomeStandardArgumentDefinitions.SNP_FILE_LONG_NAME, + shortName = ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, + optional = false + ) + protected File snpFile; + + @Argument( + doc = "Output file for base counts at called heterozygous SNP sites (normal).", + fullName = ExomeStandardArgumentDefinitions.NORMAL_ALLELIC_COUNTS_FILE_LONG_NAME, + shortName = ExomeStandardArgumentDefinitions.NORMAL_ALLELIC_COUNTS_FILE_SHORT_NAME, + optional = true + ) + protected File normalHetOutputFile; + + @Argument( + doc = "Output file for base counts at called heterozygous SNP sites (tumor).", + fullName = ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_LONG_NAME, + shortName = ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_SHORT_NAME, + optional = true + ) + protected File tumorHetOutputFile; + + @Argument( + doc = "Minimum read depth; SNP sites with lower read depths will be ignored.", + fullName = READ_DEPTH_THRESHOLD_FULL_NAME, + shortName = READ_DEPTH_THRESHOLD_SHORT_NAME, + optional = true + ) + protected int readDepthThreshold = 15; + + @Argument( + doc = "Minimum mapping quality; reads with lower quality will be filtered out of pileup.", + shortName = MINIMUM_MAPPING_QUALITY_SHORT_NAME, + fullName = MINIMUM_MAPPING_QUALITY_FULL_NAME, + optional = true + ) + protected int minimumMappingQuality = 30; + + @Argument( + doc = "Minimum base quality; base calls with lower quality will be filtered out of pileup.", + shortName = MINIMUM_BASE_QUALITY_SHORT_NAME, + fullName = MINIMUM_BASE_QUALITY_FULL_NAME, + optional = true + ) + protected int minimumBaseQuality = 20; + + @Argument( + doc = "Validation stringency for all BAM files read by this program. Setting stringency to SILENT " + + "can improve performance when processing a BAM file in which variable-length data (read, qualities, tags) " + + "do not otherwise need to be decoded.", + common=true) + protected ValidationStringency VALIDATION_STRINGENCY = ReadConstants.DEFAULT_READ_VALIDATION_STRINGENCY; + + @Argument( + doc = "Heterozygosous SNP calling stringency.", + fullName = HET_CALLING_STRINGENCY_FULL_NAME, + shortName = HET_CALLING_STRINGENCY_SHORT_NAME, + optional = true + ) + protected double hetCallingStringency = 5; + + @Argument( + doc = "Estimated minimum abnormal cell fraction (for building the allele fraction prior; to be used for " + + "tumor-only cases)", + fullName = MINIMUM_ABNORMAL_FRACTION_FULL_NAME, + shortName = MINIMUM_ABNORMAL_FRACTION_SHORT_NAME, + optional = true + ) + protected double minimumAbnormalFraction = 0.5; + + @Argument( + doc = "Estimated maximum abnormal cell fraction (for building the allele fraction prior; to be used for " + + "tumor-only cases)", + fullName = MAXIMUM_ABNORMAL_FRACTION_FULL_NAME, + shortName = MAXIMUM_ABNORMAL_FRACTION_SHORT_NAME, + optional = true + ) + protected double maximumAbnormalFraction = 0.8; + + @Argument( + doc = "Estimated maximum copy number for either homologs in the abnormal portion of the sample (for " + + "building the allele fraction prior; to be used for tumor-only cases)", + fullName = MAXIMUM_COPY_NUMBER_FULL_NAME, + shortName = MAXIMUM_COPY_NUMBER_SHORT_NAME, + optional = true + ) + protected int maximumCopyNumber = 2; + + @Argument( + doc = "Integration quadrature order; a good choice is the typical read depth (to be used for tumor-only cases)", + fullName = QUADRATURE_ORDER_FULL_NAME, + shortName = QUADRATURE_ORDER_SHORT_NAME, + optional = true + ) + protected int quadratureOrder = 200; + + @Argument( + doc = "(Experimental) error probability adjustment factor (could be any positive value)", + fullName = ERROR_PROBABILITY_ADJUSTMENT_FACTOR_FULL_NAME, + shortName = ERROR_PROBABILITY_ADJUSTMENT_FACTOR_SHORT_NAME, + optional = true + ) + protected double errorProbabilityAdjustmentFactor = 1.0; + + /** + * The normal-only workflow + */ + private void runNormalOnly() { + final BayesianHetPulldownCalculator normalHetPulldownCalculator; + final Pulldown normalHetPulldown; + + normalHetPulldownCalculator = new BayesianHetPulldownCalculator(REFERENCE_ARGUMENTS.getReferenceFile(), + IntervalList.fromFile(snpFile), minimumMappingQuality, minimumBaseQuality, readDepthThreshold, + VALIDATION_STRINGENCY, errorProbabilityAdjustmentFactor, + new BalancedHeterozygousPileupPriorModel()); + + logger.info("Calculating the Het pulldown from the normal BAM file using the BALANCED prior..."); + normalHetPulldown = normalHetPulldownCalculator.getHetPulldown(normalBamFile, hetCallingStringency); + + logger.info("Writing Het pulldown from normal reads to " + normalHetOutputFile.toString()); + normalHetPulldown.write(normalHetOutputFile, AllelicCountTableColumns.AllelicCountTableVerbosity.FULL); + } + + /** + * The tumor-only workflow + */ + private void runTumorOnly() { + final BayesianHetPulldownCalculator tumorHetPulldownCalculator; + final Pulldown tumorHetPulldown; + + tumorHetPulldownCalculator = new BayesianHetPulldownCalculator(REFERENCE_ARGUMENTS.getReferenceFile(), + IntervalList.fromFile(snpFile), minimumMappingQuality, minimumBaseQuality, readDepthThreshold, + VALIDATION_STRINGENCY, errorProbabilityAdjustmentFactor, + new HeterogeneousHeterozygousPileupPriorModel(minimumAbnormalFraction, maximumAbnormalFraction, + maximumCopyNumber, quadratureOrder)); + + logger.info("Calculating the Het pulldown from the tumor BAM file using the HETEROGENEOUS prior..."); + tumorHetPulldown = tumorHetPulldownCalculator.getHetPulldown(tumorBamFile, hetCallingStringency); + + logger.info("Writing Het pulldown from tumor reads to " + tumorHetOutputFile.toString()); + tumorHetPulldown.write(tumorHetOutputFile, AllelicCountTableColumns.AllelicCountTableVerbosity.FULL); + } + + /** + * The matched norrmal-tumor workflow + */ + private void runMatchedNormalTumor() { + final BayesianHetPulldownCalculator normalHetPulldownCalculator, tumorHetPulldownCalculator; + final Pulldown normalHetPulldown, tumorHetPulldown; + + normalHetPulldownCalculator = new BayesianHetPulldownCalculator(REFERENCE_ARGUMENTS.getReferenceFile(), + IntervalList.fromFile(snpFile), minimumMappingQuality, minimumBaseQuality, readDepthThreshold, + VALIDATION_STRINGENCY, errorProbabilityAdjustmentFactor, + new BalancedHeterozygousPileupPriorModel()); + + logger.info("Calculating the Het pulldown from the normal BAM file using the BALANCED prior..."); + normalHetPulldown = normalHetPulldownCalculator.getHetPulldown(normalBamFile, hetCallingStringency); + + logger.info("Writing Het pulldown from normal reads to " + normalHetOutputFile.toString()); + normalHetPulldown.write(normalHetOutputFile, AllelicCountTableColumns.AllelicCountTableVerbosity.FULL); + + tumorHetPulldownCalculator = new BayesianHetPulldownCalculator(REFERENCE_ARGUMENTS.getReferenceFile(), + normalHetPulldown.getIntervals(), minimumMappingQuality, minimumBaseQuality, readDepthThreshold, + VALIDATION_STRINGENCY, errorProbabilityAdjustmentFactor, + new BalancedHeterozygousPileupPriorModel()); + + logger.info("Calculating the Het pulldown from the tumor BAM file on Hets detected in the normal BAM file..."); + tumorHetPulldown = tumorHetPulldownCalculator.getTumorHetPulldownFromNormalPulldown(tumorBamFile, + normalHetPulldown); + + logger.info("Writing Het pulldown from tumor reads to " + tumorHetOutputFile.toString()); + tumorHetPulldown.write(tumorHetOutputFile, AllelicCountTableColumns.AllelicCountTableVerbosity.INTERMEDIATE); + } + + @Override + protected Object doWork() { + /* check for illegal arguments */ + if (normalBamFile == null && tumorBamFile == null) { + throw new UserException.BadArgumentValue(String.format("You must provide at least one normal (argument %s)" + + " or tumor (argument %s) alignment file.", + ExomeStandardArgumentDefinitions.NORMAL_BAM_FILE_LONG_NAME, + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_LONG_NAME)); + } + if (normalBamFile != null && normalHetOutputFile == null) { + throw new UserException.CommandLineException(String.format("If the normal BAM file is provided, the normal" + + " Het pulldown output file (argument %s) must also be provided.", + ExomeStandardArgumentDefinitions.NORMAL_ALLELIC_COUNTS_FILE_LONG_NAME)); + } + if (tumorBamFile != null && tumorHetOutputFile == null) { + throw new UserException.CommandLineException(String.format("If the tumor BAM file is provided, the tumor" + + " Het pulldown output file (argument %s) must also be provided.", + ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_LONG_NAME)); + } + + /* determine the job type */ + if (normalBamFile != null && tumorBamFile != null) { /* both normal and tumor BAM files are provided */ + logger.info("MATCHED_NORMAL_TUMOR mode selected."); + runMatchedNormalTumor(); + } else if (normalBamFile != null) { /* only the normal BAM file is provided */ + logger.info("NORMAL_ONLY mode selected."); + runNormalOnly(); + } else { /* only the tumor BAM file is provided */ + logger.info("TUMOR_ONLY mode selected."); + runTumorOnly(); + } + + return "SUCCESS"; + } +} diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/GetHetCoverage.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/GetHetCoverage.java index ee82cafb05d..17fac83efe0 100644 --- a/src/main/java/org/broadinstitute/hellbender/tools/exome/GetHetCoverage.java +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/GetHetCoverage.java @@ -8,6 +8,7 @@ import org.broadinstitute.hellbender.cmdline.programgroups.CopyNumberProgramGroup; import org.broadinstitute.hellbender.exceptions.UserException; import org.broadinstitute.hellbender.utils.read.ReadConstants; +import org.broadinstitute.hellbender.tools.exome.AllelicCountTableColumns.AllelicCountTableVerbosity; import java.io.File; @@ -136,7 +137,7 @@ protected Object doWork() { logger.info("Getting normal het pulldown..."); final Pulldown normalHetPulldown = hetPulldown.getNormal(normalBAMFile, pvalThreshold, minimumRawReads); - normalHetPulldown.write(normalHetOutputFile); + normalHetPulldown.write(normalHetOutputFile, AllelicCountTableVerbosity.BASIC); logger.info("Normal het pulldown written to " + normalHetOutputFile.toString()); if (doTumorPulldown) { @@ -144,7 +145,7 @@ protected Object doWork() { logger.info("Getting tumor het pulldown..."); final Pulldown tumorHetPulldown = hetPulldown.getTumor(tumorBAMFile, normalHetIntervals, minimumRawReads); - tumorHetPulldown.write(tumorHetOutputFile); + tumorHetPulldown.write(tumorHetOutputFile, AllelicCountTableVerbosity.BASIC); logger.info("Tumor het pulldown written to " + tumorHetOutputFile.toString()); } diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/HetPulldownCalculator.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/HetPulldownCalculator.java index 5f98ea1d3db..b7f061bc302 100644 --- a/src/main/java/org/broadinstitute/hellbender/tools/exome/HetPulldownCalculator.java +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/HetPulldownCalculator.java @@ -215,8 +215,9 @@ private Pulldown getHetPulldown(final File bamFile, final IntervalList snpInterv final int refReadCount = (int) baseCounts.get(refBase); final int altReadCount = totalBaseCount - refReadCount; - hetPulldown.add(new SimpleInterval(locus.getSequenceName(), locus.getPosition(), locus.getPosition()), - refReadCount, altReadCount); + hetPulldown.add(new AllelicCount( + new SimpleInterval(locus.getSequenceName(), locus.getPosition(), locus.getPosition()), + refReadCount, altReadCount)); } logger.info(locusCount + " covered sites out of " + totalNumberOfSNPs + " total sites were examined."); return hetPulldown; diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/HeterogeneousHeterozygousPileupPriorModel.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/HeterogeneousHeterozygousPileupPriorModel.java new file mode 100644 index 00000000000..258eb513fc7 --- /dev/null +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/HeterogeneousHeterozygousPileupPriorModel.java @@ -0,0 +1,189 @@ +package org.broadinstitute.hellbender.tools.exome; + +import com.google.common.annotations.VisibleForTesting; +import org.apache.commons.lang3.tuple.Pair; +import org.apache.commons.math3.analysis.integration.gauss.GaussIntegrator; +import org.apache.commons.math3.analysis.integration.gauss.GaussIntegratorFactory; +import org.apache.commons.math3.util.FastMath; +import org.broadinstitute.hellbender.utils.GATKProtectedMathUtils; +import org.broadinstitute.hellbender.utils.param.ParamUtils; + +import java.util.ArrayList; +import java.util.Collection; +import java.util.List; +import java.util.stream.Collectors; +import java.util.stream.IntStream; + +/** + * Heterogeneous model prior for heterozygous pileups. + * + * This prior is suitable for detecting heterozygous sites from reads that come from tumor or contaminated + * normal samples. + * + * TODO + * + *
    + *
  • The quadrature order can be adaptively chosen based on the pileup size and the accuracy + * required for likelihood estimation. In theory, a Gaussian quadrature of order N yields + * the exact result for a pileup of size 2N.
    • + *
+ * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + */ +public final class HeterogeneousHeterozygousPileupPriorModel extends HeterozygousPileupPriorModel { + + /* these are for building a prior for allele fraction */ + private final double minAbnormalFraction; + private final double maxAbnormalFraction; + private final double maxCopyNumber; + private final double minHetAlleleFraction; + private final double breakpointHetAlleleFraction; + + /* integration quadrature */ + @VisibleForTesting + final List gaussIntegrationWeights = new ArrayList<>(); + @VisibleForTesting + final List gaussIntegrationLogWeights = new ArrayList<>(); + @VisibleForTesting + final List gaussIntegrationAbscissas = new ArrayList<>(); + + /* allele fraction prior for Het sites */ + @VisibleForTesting + final List alleleFractionPriors = new ArrayList<>(); + @VisibleForTesting + final List alleleFractionLogPriors = new ArrayList<>(); + + /* minimum order of the integration quadrature */ + private static final int MIN_QUADRATURE_ORDER = 50; + + /** + * Initialize the prior + * @param minAbnormalFraction estimated minimum fraction of non-germline cells in the sample + * @param maxAbnormalFraction estimated maximum fraction of non-germline cells in the sample + * @param maxCopyNumber estimated maximum copy number in non-germline events (note: we use a flat probability + * function for the copy number. using a large value of maxCopyNumber will result in a + * significant spread of the minor allele fraction prior around 1/2. it is recommended not + * to use values > 4). + * @param quadratureOrder the order of quadrature used in numerical integrations + */ + public HeterogeneousHeterozygousPileupPriorModel(final double minAbnormalFraction, final double maxAbnormalFraction, + final int maxCopyNumber, final int quadratureOrder) { + this.minAbnormalFraction = ParamUtils.inRange(minAbnormalFraction, 0.0, 1.0, "Minimum fraction of abnormal" + + " cells must be between 0 and 1."); + this.maxAbnormalFraction = ParamUtils.inRange(maxAbnormalFraction, this.minAbnormalFraction, 1.0, "Maximum fraction of abnormal" + + " cells must be greater than the provided minimum and less than 1."); + this.maxCopyNumber = ParamUtils.isPositive(maxCopyNumber, "Maximum copy number must be positive"); + + /* auxiliary derived members */ + this.minHetAlleleFraction = (1 - this.maxAbnormalFraction) / (this.maxCopyNumber * this.maxAbnormalFraction + + 2 * (1 - this.maxAbnormalFraction)); + this.breakpointHetAlleleFraction = (1 - this.minAbnormalFraction) / (this.maxCopyNumber * this.minAbnormalFraction + + 2 * (1 - this.minAbnormalFraction)); + + /* initialize the integration quadrature and calculate the allele fraction prior on the abscissas */ + initializeIntegrationQuadrature(ParamUtils.isPositive(quadratureOrder - MIN_QUADRATURE_ORDER, + "Quadrature order must be greater than " + MIN_QUADRATURE_ORDER) + MIN_QUADRATURE_ORDER); + initializeHetAlleleFractionPrior(); + } + + /** + * Initilizes the quadrature for calculating allele ratio integrals in + * {@link HeterogeneousHeterozygousPileupPriorModel#getHetLogLikelihood(List)} + * + * @param numIntegPoints number of points in the quadrature + */ + private void initializeIntegrationQuadrature(final int numIntegPoints) { + /* get Gauss-Legendre quadrature factory of order @numIntegPoints */ + final GaussIntegratorFactory integratorFactory = new GaussIntegratorFactory(); + final GaussIntegrator gaussIntegrator = integratorFactory.legendre(numIntegPoints, + minHetAlleleFraction, 1.0 - minHetAlleleFraction); + + /* abscissas */ + gaussIntegrationAbscissas.clear(); + gaussIntegrationAbscissas.addAll(IntStream.range(0, numIntegPoints). + mapToDouble(gaussIntegrator::getPoint).boxed().collect(Collectors.toList())); + + /* weights */ + gaussIntegrationWeights.clear(); + gaussIntegrationWeights.addAll(IntStream.range(0, numIntegPoints). + mapToDouble(gaussIntegrator::getWeight).boxed().collect(Collectors.toList())); + + /* log of weights */ + gaussIntegrationLogWeights.clear(); + gaussIntegrationLogWeights.addAll(gaussIntegrationWeights.stream(). + mapToDouble(FastMath::log).boxed().collect(Collectors.toList())); + } + + /** + * (advanced) Calculate a simple prior probability distribution for the allele fraction based on + * (1) purity of the sample, and (2) maximum copy number for abnormal cells. + * (See CNV-methods.pdf for details.) + * + * @param alleleFraction allele fraction to calculate the prior probability distribution on + * @return allele fraction prior probability distribution + */ + private double calculateAlleleFractionPriorDistribution(final double alleleFraction) { + final double minorAlleleFraction = (alleleFraction < 0.5) ? alleleFraction : 1 - alleleFraction; + if (minorAlleleFraction < minHetAlleleFraction) { + return 0; + } else if (minorAlleleFraction < breakpointHetAlleleFraction) { + final double denom = 2 * FastMath.pow((1 - minorAlleleFraction) * minorAlleleFraction * maxCopyNumber, 2) * + maxAbnormalFraction * (maxAbnormalFraction - minAbnormalFraction); + final double num = (-1 + (-1 + minorAlleleFraction * maxCopyNumber) * maxAbnormalFraction) * + (-1 + maxAbnormalFraction + minorAlleleFraction * (2 + (-2 + maxCopyNumber) * maxAbnormalFraction)) + + 2 * (1 + minorAlleleFraction * (-2 + minorAlleleFraction * maxCopyNumber)) * maxAbnormalFraction * + FastMath.log(FastMath.abs(((1 + minorAlleleFraction * (-2 + maxCopyNumber)) * maxAbnormalFraction)) / + (1 - 2 * minorAlleleFraction)); + return num / denom; + } else { /* breakpointHetAlleleFraction < minorAlleleFraction < 1/2 */ + final double denom = 2 * FastMath.pow((1 - minorAlleleFraction) * minorAlleleFraction * maxCopyNumber, 2) * + maxAbnormalFraction * minAbnormalFraction * (maxAbnormalFraction - minAbnormalFraction); + final double num = (maxAbnormalFraction - minAbnormalFraction) * (-1 + 2 * minorAlleleFraction + + (1 + minorAlleleFraction * (-2 + maxCopyNumber)) * (-1 + minorAlleleFraction * maxCopyNumber) * + maxAbnormalFraction * minAbnormalFraction) + 2 * (1 + minorAlleleFraction * (-2 + minorAlleleFraction * + maxCopyNumber)) * maxAbnormalFraction * minAbnormalFraction * FastMath.log(maxAbnormalFraction / minAbnormalFraction); + return num / denom; + } + } + /** + * Calculate the allele fraction distribution function and its log on the abscissas on the integration + * quadrature + */ + private void initializeHetAlleleFractionPrior() { + alleleFractionPriors.clear(); + alleleFractionPriors.addAll(gaussIntegrationAbscissas.stream() + .mapToDouble(this::calculateAlleleFractionPriorDistribution) + .boxed().collect(Collectors.toList())); + + /* calculate the log prior */ + alleleFractionLogPriors.clear(); + alleleFractionLogPriors.addAll(alleleFractionPriors.stream() + .map(FastMath::log).collect(Collectors.toList())); + } + + /** + * Marginalize allele fraction by integrating the precomputed allele fraction prior weighted with the + * likelihoods of the alt/ret portion of reads in the pileup + * (see CNV-method.pdf for details) + * + * @param coeffs list of (alpha_k, beta_k) tuples + * @return log likelihood + */ + @Override + public double getHetLogLikelihood(final Collection> coeffs) { + final ArrayList refAltLogLikelihoodList = new ArrayList<>(gaussIntegrationAbscissas.size()); + refAltLogLikelihoodList.addAll( + gaussIntegrationAbscissas.stream() + .map(f -> getHetLogLikelihoodFixedAlleleFraction(f, coeffs)) + .collect(Collectors.toList())); + + final ArrayList logLikelihoodIntegrandWithPriorAndWeights = new ArrayList<>(gaussIntegrationAbscissas.size()); + logLikelihoodIntegrandWithPriorAndWeights.addAll( + IntStream.range(0, gaussIntegrationAbscissas.size()) + .mapToDouble(i -> refAltLogLikelihoodList.get(i) + gaussIntegrationLogWeights.get(i) + + alleleFractionLogPriors.get(i)) + .boxed().collect(Collectors.toList())); + + return GATKProtectedMathUtils.logSumExp(logLikelihoodIntegrandWithPriorAndWeights); + } +} diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/HeterozygousPileupPriorModel.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/HeterozygousPileupPriorModel.java new file mode 100644 index 00000000000..0a83bb3d53c --- /dev/null +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/HeterozygousPileupPriorModel.java @@ -0,0 +1,53 @@ +package org.broadinstitute.hellbender.tools.exome; + +import org.apache.commons.lang3.tuple.Pair; +import org.apache.commons.math3.util.FastMath; + +import java.util.Collection; + +/** + * Model prior for heterozygous pileups + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + */ + +public abstract class HeterozygousPileupPriorModel { + + /** + * Calculate the log likelihood for a pileup being heterzygous given a fixed allele fraction. + * + * Entry k in the pileup gives an additive contribution l_k, + * + * l_k = log(alpha_k * alleleFraction + beta_k), + * + * to the log likelihood. The list of (alpha_k, beta_k) tuples are provided by {@code coeffs}. These + * coefficients are calculated according to the read and mapping qualtities (see CNV-methods.pdf for details). + * + * Note that the full heterozygosity likelihood must be further adjusted according to the non-ref and non-alt + * reads. For example, see {@link BayesianHetPulldownCalculator::getHetLogLikelihood}. + * + * @param alleleFraction the ref to alt allele fraction + * @param coeffs list of (alpha, beta) tuples + * @return any double value + */ + protected double getHetLogLikelihoodFixedAlleleFraction(final double alleleFraction, + final Collection> coeffs) { + return coeffs.stream() + .mapToDouble(dat -> dat.getLeft() + alleleFraction * dat.getRight()) + .map(FastMath::log) + .sum(); + } + + /** + * To be implemented by concrete models that extend this class. + * + * Note: concrete prior models weight the fixed allele fraction likelihoods, as given by + * {@link HeterozygousPileupPriorModel#getHetLogLikelihoodFixedAlleleFraction(double, Collection)}, + * with the to-be-implemented allele fraction prior. For example, see + * {@link HeterogeneousHeterozygousPileupPriorModel}. + * + * @param coeffs list of (alpha, beta) tuples + * @return any double value + */ + public abstract double getHetLogLikelihood(final Collection> coeffs); +} diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/allelefraction/AlleleFractionLikelihoods.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/allelefraction/AlleleFractionLikelihoods.java index 72a554c6980..765db2f1e38 100644 --- a/src/main/java/org/broadinstitute/hellbender/tools/exome/allelefraction/AlleleFractionLikelihoods.java +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/allelefraction/AlleleFractionLikelihoods.java @@ -179,7 +179,7 @@ protected static double biasPosteriorEffectiveBeta(final double lambda0, final d * @return the log of the likelihood at this het site, marginalized over indicator states. */ public static double collapsedHetLogLikelihood(final AlleleFractionState state, final int segment, final AllelicCount count, final AllelicPanelOfNormals allelicPON) { - return GATKProtectedMathUtils.naturalLogSumExp( + return GATKProtectedMathUtils.logSumExp( hetLogLikelihood(state, segment, count, AlleleFractionIndicator.ALT_MINOR, allelicPON), hetLogLikelihood(state, segment, count, AlleleFractionIndicator.REF_MINOR, allelicPON), hetLogLikelihood(state, segment, count, AlleleFractionIndicator.OUTLIER, allelicPON)); diff --git a/src/main/java/org/broadinstitute/hellbender/tools/exome/allelefraction/MinorAlleleFractionCache.java b/src/main/java/org/broadinstitute/hellbender/tools/exome/allelefraction/MinorAlleleFractionCache.java index 1ba43295fa2..409a1ec8124 100644 --- a/src/main/java/org/broadinstitute/hellbender/tools/exome/allelefraction/MinorAlleleFractionCache.java +++ b/src/main/java/org/broadinstitute/hellbender/tools/exome/allelefraction/MinorAlleleFractionCache.java @@ -59,7 +59,7 @@ private static double estimateMinorAlleleFraction(final int a, final int r, fina a * logf + r * (logOneMinusf + logBias) - (a + r) * logAltMinorDenominatorTerm; final double refMinorLogLikelihood = r * (logf + logBias) + a * logOneMinusf - (a + r) * logRefMinorDenominatorTerm; - return GATKProtectedMathUtils.naturalLogSumExp(altMinorLogLikelihood, refMinorLogLikelihood); + return GATKProtectedMathUtils.logSumExp(altMinorLogLikelihood, refMinorLogLikelihood); }); return OPTIMIZER.optimize(objective, GoalType.MAXIMIZE, searchInterval, BRENT_MAX_EVAL).getPoint(); diff --git a/src/main/java/org/broadinstitute/hellbender/utils/GATKProtectedMathUtils.java b/src/main/java/org/broadinstitute/hellbender/utils/GATKProtectedMathUtils.java index 0479a27f83b..386099cb7ab 100644 --- a/src/main/java/org/broadinstitute/hellbender/utils/GATKProtectedMathUtils.java +++ b/src/main/java/org/broadinstitute/hellbender/utils/GATKProtectedMathUtils.java @@ -3,8 +3,11 @@ import org.apache.commons.math3.linear.RealMatrix; import org.apache.commons.math3.stat.descriptive.moment.Variance; import org.apache.commons.math3.stat.descriptive.rank.Percentile; +import org.apache.commons.math3.util.FastMath; +import java.util.ArrayList; import java.util.Collection; +import java.util.Collections; import java.util.stream.IntStream; /** @@ -14,7 +17,7 @@ public class GATKProtectedMathUtils { /** - * Computes ln(Sum_i(e^a_i)) trying to avoid underflow issues by using the log-sum-exp trick. + * Computes $\log(\sum_i e^{a_i})$ trying to avoid underflow issues by using the log-sum-exp trick. * *

* This trick consists on shift all the log values by the maximum so that exponent values are @@ -23,7 +26,7 @@ public class GATKProtectedMathUtils { *

* @return any double value. */ - public static double naturalLogSumExp(final double ... values) { + public static double logSumExp(final double ... values) { double max = MathUtils.arrayMax(Utils.nonNull(values)); double sum = 0.0; for (int i = 0; i < values.length; ++i) { @@ -33,6 +36,17 @@ public static double naturalLogSumExp(final double ... values) { } return max + Math.log(sum); } + + public static double logSumExp(final Collection values) { + double max = Collections.max(values); + double sum = 0.0; + for (final double val : values) { + if (val != Double.NEGATIVE_INFINITY) { + sum += java.lang.Math.exp(val - max); + } + } + return max + Math.log(sum); + } public static double interquartileRange(final double ... values) { final Percentile percentile = new Percentile(); diff --git a/src/main/java/org/broadinstitute/hellbender/utils/hmm/ForwardBackwardAlgorithm.java b/src/main/java/org/broadinstitute/hellbender/utils/hmm/ForwardBackwardAlgorithm.java index d58e8fc6f52..6431034e1a3 100644 --- a/src/main/java/org/broadinstitute/hellbender/utils/hmm/ForwardBackwardAlgorithm.java +++ b/src/main/java/org/broadinstitute/hellbender/utils/hmm/ForwardBackwardAlgorithm.java @@ -336,7 +336,7 @@ private static double[][] calculateLogForwardProbabilities( + model.logTransitionProbability(states.get(previousStateIndex), previousPosition, thisState, thisPosition); } - result[thisPositionIndex][thisStateIndex] = GATKProtectedMathUtils.naturalLogSumExp(logSumBuffer) + result[thisPositionIndex][thisStateIndex] = GATKProtectedMathUtils.logSumExp(logSumBuffer) + model.logEmissionProbability(data.get(thisPositionIndex), thisState, thisPosition); } } @@ -397,7 +397,7 @@ private static double[][] calculateLogBackwardProbabilities(final Hidd + model.logEmissionProbability(dataList.get(nextPositionIndex), states.get(nextStateIndex), nextPosition); } - result[thisPositionIndex][thisStateIndex] = GATKProtectedMathUtils.naturalLogSumExp(logSumBuffer); + result[thisPositionIndex][thisStateIndex] = GATKProtectedMathUtils.logSumExp(logSumBuffer); } } return result; @@ -464,7 +464,7 @@ private static double[] calculateLogDataLikelihood(final double[][] logForwardPr .mapToDouble(j -> logBackwardProbabilities[i][j] + logForwardProbabilities[i][j]) .toArray()) - .mapToDouble(GATKProtectedMathUtils::naturalLogSumExp) + .mapToDouble(GATKProtectedMathUtils::logSumExp) .toArray(); } @@ -624,7 +624,7 @@ public double logConstrainedProbability(final int startIndex, final List> // by the emission probability of the current datum. currentLikelihoods = currentStates.stream() .mapToDouble(thisState -> - GATKProtectedMathUtils.naturalLogSumExp(IntStream.range(0, previousStates.size()) + GATKProtectedMathUtils.logSumExp(IntStream.range(0, previousStates.size()) .mapToDouble(previousStateIndex -> { final S previousState = previousStates.get(previousStateIndex); return previousLikelihoods[previousStateIndex] @@ -640,7 +640,7 @@ public double logConstrainedProbability(final int startIndex, final List> for (int i = 0; i < currentLikelihoods.length; i++) { currentLikelihoods[i] += logBackwardProbabilities[lastIndex][stateIndex.getInt(lastStates.get(i))]; } - return GATKProtectedMathUtils.naturalLogSumExp(currentLikelihoods) - logDataLikelihood[lastIndex]; + return GATKProtectedMathUtils.logSumExp(currentLikelihoods) - logDataLikelihood[lastIndex]; } } diff --git a/src/test/java/org/broadinstitute/hellbender/tools/exome/AllelicCountCollectionUnitTest.java b/src/test/java/org/broadinstitute/hellbender/tools/exome/AllelicCountCollectionUnitTest.java index c41352e95cc..cff10bba2da 100644 --- a/src/test/java/org/broadinstitute/hellbender/tools/exome/AllelicCountCollectionUnitTest.java +++ b/src/test/java/org/broadinstitute/hellbender/tools/exome/AllelicCountCollectionUnitTest.java @@ -1,6 +1,7 @@ package org.broadinstitute.hellbender.tools.exome; import org.broadinstitute.hellbender.exceptions.UserException; +import org.broadinstitute.hellbender.utils.Nucleotide; import org.broadinstitute.hellbender.utils.SimpleInterval; import org.broadinstitute.hellbender.utils.test.BaseTest; import org.testng.Assert; @@ -12,11 +13,14 @@ * Unit tests for {@link AllelicCountCollection}. * * @author Samuel Lee <slee@broadinstitute.org> + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> */ public class AllelicCountCollectionUnitTest extends BaseTest { private static final String TEST_SUB_DIR = publicTestDir + "org/broadinstitute/hellbender/tools/exome"; - private static final File SNPS_FILE = new File(TEST_SUB_DIR, "snps.tsv"); + private static final File BASIC_SNPS_FILE = new File(TEST_SUB_DIR, "snps-basic.tsv"); + private static final File INTERMEDIATE_SNPS_FILE = new File(TEST_SUB_DIR, "snps-intermediate.tsv"); + private static final File FULL_SNPS_FILE = new File(TEST_SUB_DIR, "snps-full.tsv"); private static final File SNPS_WITH_MISSING_COLUMN_FILE = new File(TEST_SUB_DIR, "snps-with-missing-column.tsv"); @Test(expectedExceptions = UserException.class) @@ -28,25 +32,67 @@ public void testReadWithMissingColumns() throws Exception { public void testAddAndGetCounts() throws Exception { final AllelicCountCollection counts = new AllelicCountCollection(); final AllelicCount count = new AllelicCount(new SimpleInterval("1", 1, 1), 1, 1); - counts.add(new SimpleInterval("1", 1, 1), 1, 1); + counts.add(new AllelicCount(new SimpleInterval("1", 1, 1), 1, 1)); Assert.assertEquals(count, counts.getCounts().get(0)); } @Test - public void testReadAndWrite() throws Exception { + public void testReadAndWriteBasicCollection() throws Exception { final File tempFile = createTempFile("allelic-count-collection-test", "tsv"); - final AllelicCountCollection snps = new AllelicCountCollection(SNPS_FILE); - snps.write(tempFile); + final AllelicCountCollection snps = new AllelicCountCollection(BASIC_SNPS_FILE); + snps.write(tempFile, AllelicCountTableColumns.AllelicCountTableVerbosity.BASIC); final AllelicCountCollection snpsWritten = new AllelicCountCollection(tempFile); final AllelicCountCollection snpsExpected = new AllelicCountCollection(); - snpsExpected.add(new SimpleInterval("1", 881918, 881918), 14, 21); - snpsExpected.add(new SimpleInterval("1", 909238, 909238), 13, 11); - snpsExpected.add(new SimpleInterval("1", 934940, 934940), 14, 0); - snpsExpected.add(new SimpleInterval("1", 949608, 949608), 20, 14); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 881918, 881918), 14, 21)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 909238, 909238), 13, 11)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 934940, 934940), 14, 0)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 949608, 949608), 20, 14)); Assert.assertEquals(snpsWritten, snpsExpected); } -} \ No newline at end of file + + @Test + public void testReadAndWriteItermediateCollection() throws Exception { + final File tempFile = createTempFile("allelic-count-collection-test", "tsv"); + final AllelicCountCollection snps = new AllelicCountCollection(INTERMEDIATE_SNPS_FILE); + snps.write(tempFile, AllelicCountTableColumns.AllelicCountTableVerbosity.INTERMEDIATE); + + final AllelicCountCollection snpsWritten = new AllelicCountCollection(tempFile); + + final AllelicCountCollection snpsExpected = new AllelicCountCollection(); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 881918, 881918), 14, 21, + Nucleotide.A, Nucleotide.C, 35)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 909238, 909238), 13, 11, + Nucleotide.T, Nucleotide.G, 26)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 934940, 934940), 14, 0, + Nucleotide.A, Nucleotide.G, 17)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 949608, 949608), 20, 14, + Nucleotide.G, Nucleotide.T, 34)); + + Assert.assertEquals(snpsWritten, snpsExpected); + } + + @Test + public void testReadAndWriteFullCollection() throws Exception { + final File tempFile = createTempFile("allelic-count-collection-test", "tsv"); + final AllelicCountCollection snps = new AllelicCountCollection(FULL_SNPS_FILE); + snps.write(tempFile, AllelicCountTableColumns.AllelicCountTableVerbosity.FULL); + + final AllelicCountCollection snpsWritten = new AllelicCountCollection(tempFile); + + final AllelicCountCollection snpsExpected = new AllelicCountCollection(); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 881918, 881918), 14, 21, + Nucleotide.A, Nucleotide.C, 35, 12.0)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 909238, 909238), 13, 11, + Nucleotide.T, Nucleotide.G, 26, 120.5)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 934940, 934940), 14, 0, + Nucleotide.A, Nucleotide.G, 17, -16.1)); + snpsExpected.add(new AllelicCount(new SimpleInterval("1", 949608, 949608), 20, 14, + Nucleotide.G, Nucleotide.T, 34, 54.3)); + + Assert.assertEquals(snpsWritten, snpsExpected); + } +} diff --git a/src/test/java/org/broadinstitute/hellbender/tools/exome/AllelicCountUnitTest.java b/src/test/java/org/broadinstitute/hellbender/tools/exome/AllelicCountUnitTest.java index 8755c4b2c68..51454a5bea7 100644 --- a/src/test/java/org/broadinstitute/hellbender/tools/exome/AllelicCountUnitTest.java +++ b/src/test/java/org/broadinstitute/hellbender/tools/exome/AllelicCountUnitTest.java @@ -1,5 +1,6 @@ package org.broadinstitute.hellbender.tools.exome; +import org.broadinstitute.hellbender.utils.Nucleotide; import org.broadinstitute.hellbender.utils.SimpleInterval; import org.testng.Assert; import org.testng.annotations.Test; @@ -60,4 +61,44 @@ public void testToMinorAlleleFractionTargetCoverage() { Assert.assertEquals(result.getName(), expected.getName()); Assert.assertEquals(result.getCoverage(), expected.getCoverage()); } + + @Test + public void testEquality() { + final SimpleInterval interval = new SimpleInterval("contig", 1, 2); + + /* no metadata */ + Assert.assertEquals( + new AllelicCount(interval, 5, 10), + new AllelicCount(interval, 5, 10)); + Assert.assertNotEquals( + new AllelicCount(interval, 5, 10), + new AllelicCount(interval, 5, 11)); + Assert.assertNotEquals( + new AllelicCount(interval, 5, 10), + new AllelicCount(new SimpleInterval("another_contig", 1, 2), 5, 10)); + + /* metadata on one, missing on the other and same mandatory. expected equality */ + Assert.assertEquals( + new AllelicCount(interval, 5, 10), + new AllelicCount(interval, 5, 10, Nucleotide.A, Nucleotide.C, 20)); + Assert.assertEquals( + new AllelicCount(interval, 5, 10), + new AllelicCount(interval, 5, 10, Nucleotide.A, Nucleotide.C, 20, 123.1234)); + + /* different het log odds. not checking on this for equality, so expect equality */ + Assert.assertEquals( + new AllelicCount(interval, 5, 10, Nucleotide.A, Nucleotide.C, 20, 456.7890), + new AllelicCount(interval, 5, 10, Nucleotide.A, Nucleotide.C, 20, 123.1234)); + /* missing het log odds on one, expect equality */ + Assert.assertEquals( + new AllelicCount(interval, 5, 10, Nucleotide.A, Nucleotide.C, 20), + new AllelicCount(interval, 5, 10, Nucleotide.A, Nucleotide.C, 20, 123.1234)); + /* different alt/ref bases, expect inequality */ + Assert.assertNotEquals( + new AllelicCount(interval, 6, 10, Nucleotide.T, Nucleotide.C, 20), + new AllelicCount(interval, 6, 10, Nucleotide.A, Nucleotide.C, 20, 123.1234)); + Assert.assertNotEquals( + new AllelicCount(interval, 6, 10, Nucleotide.T, Nucleotide.G, 20), + new AllelicCount(interval, 6, 10, Nucleotide.T, Nucleotide.C, 20, 123.1234)); + } } \ No newline at end of file diff --git a/src/test/java/org/broadinstitute/hellbender/tools/exome/BayesianHetPulldownCalculatorUnitTest.java b/src/test/java/org/broadinstitute/hellbender/tools/exome/BayesianHetPulldownCalculatorUnitTest.java new file mode 100644 index 00000000000..5bfb031c1b7 --- /dev/null +++ b/src/test/java/org/broadinstitute/hellbender/tools/exome/BayesianHetPulldownCalculatorUnitTest.java @@ -0,0 +1,332 @@ +package org.broadinstitute.hellbender.tools.exome; + +import htsjdk.samtools.*; +import htsjdk.samtools.util.IntervalList; +import org.broadinstitute.hellbender.exceptions.UserException; +import org.broadinstitute.hellbender.utils.Nucleotide; +import org.broadinstitute.hellbender.utils.SimpleInterval; +import org.broadinstitute.hellbender.utils.test.BaseTest; +import org.omg.CORBA.SystemException; +import org.testng.Assert; +import org.testng.annotations.BeforeClass; +import org.testng.annotations.DataProvider; +import org.testng.annotations.Test; + +import java.io.File; +import java.io.FileInputStream; +import java.io.IOException; +import java.util.*; +import java.util.stream.Collectors; +import java.util.stream.IntStream; + +/** + * Unit tests for {@link BayesianHetPulldownCalculator}. + * + * The fake pileups and the likelihoods are generated based on the constants defined below and for the + * HETEROGENEOUS prior. At the moment, there are no unit test the simpler case of BALANCED prior. + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + */ +public final class BayesianHetPulldownCalculatorUnitTest extends BaseTest { + + private static final String TEST_SUB_DIR = publicTestDir + "org/broadinstitute/hellbender/tools/exome"; + + /*****************************************************************************************************************/ + + private static final File SNP_FILE = new File(TEST_SUB_DIR, "common_SNP.interval_list"); + private static final File REF_FILE = new File(hg19MiniReference); + private static final File NORMAL_BAM_FILE = new File(TEST_SUB_DIR, "normal.sorted.bam"); + private static final File TUMOR_BAM_FILE = new File(TEST_SUB_DIR, "tumor.sorted.bam"); + + private static final int READ_DEPTH_THRESHOLD = 10; + private static final int MINIMUM_MAPPING_QUALITY = 30; + private static final int MINIMUM_BASE_QUALITY = 20; + private static final int QUADRATURE_ORDER = 300; + private static final double MIN_ABNORMAL_FRACTION = 0.5; + private static final double MAX_ABNORMAL_FRACTION = 0.8; + private static final int MAX_COPY_NUMBER = 4; + private static final double ERROR_PROBABILITY_ADJUSTMENT_FACTOR = 1.0; + + private static SAMFileHeader normalHeader; + private static SAMFileHeader tumorHeader; + + private static BayesianHetPulldownCalculator calculator; + + private static int numPileupEntries; + private static List>> + fakePileupBaseQualities = new ArrayList<>(); + private static ArrayList fakePileupHetLogLikelihoodArray = new ArrayList<>(); + private static ArrayList fakePileupHomLogLikelihoodArray = new ArrayList<>(); + + /*****************************************************************************************************************/ + + private static final File FAKE_PILEUP_FILE = new File(TEST_SUB_DIR, "test_fake_generated_pileup.txt"); + + public interface StringMapper { + T of(String input); + } + + @BeforeClass + public void initHeaders() throws IOException { + try (final SamReader normalBamReader = SamReaderFactory.makeDefault().open(NORMAL_BAM_FILE); + final SamReader tumorBamReader = SamReaderFactory.makeDefault().open(TUMOR_BAM_FILE)) { + normalHeader = normalBamReader.getFileHeader(); + tumorHeader = tumorBamReader.getFileHeader(); + } + } + + @BeforeClass + public void initHetPulldownCalculator() { + calculator = new BayesianHetPulldownCalculator(REF_FILE, IntervalList.fromFile(SNP_FILE), + MINIMUM_MAPPING_QUALITY, MINIMUM_BASE_QUALITY, READ_DEPTH_THRESHOLD, + ValidationStringency.STRICT, ERROR_PROBABILITY_ADJUSTMENT_FACTOR, + new HeterogeneousHeterozygousPileupPriorModel(MIN_ABNORMAL_FRACTION, MAX_ABNORMAL_FRACTION, + MAX_COPY_NUMBER, QUADRATURE_ORDER)); + } + + /** + * load the fake fileup from file + * + * @throws IOException + */ + @BeforeClass + public void loadPileup() throws IOException { + + /* load fake pileup and likelihoods from disk */ + StringMapper stringStripper = s -> s.substring(s.indexOf(':') + 1).replaceAll("\\s+", ""); + StringMapper parseToDouble = s -> Double.parseDouble(stringStripper.of(s)); + StringMapper> parseToDoubleArray = s -> { + String[] tokenizedLine = stringStripper.of(s).split(","); + ArrayList errorList = new ArrayList<>(); + if (tokenizedLine.length >= 1 && !tokenizedLine[0].equals("")) { + errorList.addAll(Arrays.asList(tokenizedLine).stream() + .map(Double::parseDouble) + .collect(Collectors.toList())); + } + return errorList; + }; + + Scanner reader = new Scanner(new FileInputStream(FAKE_PILEUP_FILE)); + while (reader.hasNextLine()) { + + Map> baseQualities = new HashMap<>(); + + for (Nucleotide base : new Nucleotide[]{Nucleotide.A, Nucleotide.C, Nucleotide.T, Nucleotide.G}) { + + /* load base read error list */ + ArrayList readErrorList = parseToDoubleArray.of(reader.nextLine()); + + /* set the mapping error probability to 1e-6 */ + ArrayList mappingErrorList = new ArrayList<>(); + mappingErrorList.addAll(IntStream.range(0, readErrorList.size()) + .mapToDouble(i -> 1e-6).boxed().collect(Collectors.toList())); + + /* contruct the BaseQuality list */ + List baseQualityList = new ArrayList<>(); + baseQualityList.addAll(IntStream.range(0, readErrorList.size()).mapToObj(i -> new BayesianHetPulldownCalculator.BaseQuality( + readErrorList.get(i), mappingErrorList.get(i))).collect(Collectors.toList())); + + baseQualities.put(base, baseQualityList); + } + + fakePileupBaseQualities.add(baseQualities); + fakePileupHetLogLikelihoodArray.add(parseToDouble.of(reader.nextLine())); + fakePileupHomLogLikelihoodArray.add(parseToDouble.of(reader.nextLine())); + } + + numPileupEntries = fakePileupBaseQualities.size(); + } + + @DataProvider(name = "inputTestGetHomLogLikelihood") + public Object[][] inputTestGetHomLogLikelihood() { + + Nucleotide alleleRef = Nucleotide.A; + Nucleotide alleleAlt = Nucleotide.T; + double homRefPrior = 0.5; + + Object[][] out = new Object[numPileupEntries][]; + for (int i=0; i> baseQualities, + final Nucleotide alleleRef, final Nucleotide alleleAlt, + final double homRefPrior, final double expectedHomLogLikelihood) { + for (int i=0; i> baseQualities, + final Nucleotide alleleRef, final Nucleotide alleleAlt, + final double expectedHetLogLikelihood) { + for (int i=0; i> baseQualities = new HashMap<>(); + BayesianHetPulldownCalculator.BaseQuality genericBaseQuality = new BayesianHetPulldownCalculator.BaseQuality(60.0, 60.0); + + List genericBaseQualityList_0 = new ArrayList<>(); + List genericBaseQualityList_1 = new ArrayList<>(); + List genericBaseQualityList_2 = new ArrayList<>(); + List genericBaseQualityList_3 = new ArrayList<>(); + List genericBaseQualityList_4 = new ArrayList<>(); + + /* only the base counts matter; so we can use a generic BaseQuality for all lists */ + + genericBaseQualityList_1.add(genericBaseQuality); + + genericBaseQualityList_2.add(genericBaseQuality); + genericBaseQualityList_2.add(genericBaseQuality); + + genericBaseQualityList_3.add(genericBaseQuality); + genericBaseQualityList_3.add(genericBaseQuality); + genericBaseQualityList_3.add(genericBaseQuality); + + genericBaseQualityList_4.add(genericBaseQuality); + genericBaseQualityList_4.add(genericBaseQuality); + genericBaseQualityList_4.add(genericBaseQuality); + genericBaseQualityList_4.add(genericBaseQuality); + + /* test 1 */ + baseQualities.put(Nucleotide.A, genericBaseQualityList_4); + baseQualities.put(Nucleotide.C, genericBaseQualityList_2); + baseQualities.put(Nucleotide.T, genericBaseQualityList_1); + baseQualities.put(Nucleotide.G, genericBaseQualityList_1); + + Assert.assertEquals(BayesianHetPulldownCalculator.inferAltFromPileup(baseQualities, Nucleotide.A), Nucleotide.C); + Assert.assertEquals(BayesianHetPulldownCalculator.inferAltFromPileup(baseQualities, Nucleotide.C), Nucleotide.A); + Assert.assertEquals(BayesianHetPulldownCalculator.inferAltFromPileup(baseQualities, Nucleotide.T), Nucleotide.A); + Assert.assertEquals(BayesianHetPulldownCalculator.inferAltFromPileup(baseQualities, Nucleotide.G), Nucleotide.A); + + /* test 2 */ + baseQualities.put(Nucleotide.A, genericBaseQualityList_0); + baseQualities.put(Nucleotide.C, genericBaseQualityList_3); + baseQualities.put(Nucleotide.T, genericBaseQualityList_0); + baseQualities.put(Nucleotide.G, genericBaseQualityList_0); + + Assert.assertEquals(BayesianHetPulldownCalculator.inferAltFromPileup(baseQualities, Nucleotide.A), Nucleotide.C); + /* in this case, A is chosen simply because sorting places A right after C; in theory, T and G are equally + valid "guesses" */ + Assert.assertEquals(BayesianHetPulldownCalculator.inferAltFromPileup(baseQualities, Nucleotide.C), Nucleotide.A); + Assert.assertEquals(BayesianHetPulldownCalculator.inferAltFromPileup(baseQualities, Nucleotide.T), Nucleotide.C); + Assert.assertEquals(BayesianHetPulldownCalculator.inferAltFromPileup(baseQualities, Nucleotide.G), Nucleotide.C); + + } + + @Test + public void testGetHetPulldown() { + + Pulldown testPulldown, expectedPulldown; + File tempFile; + + /* write Pulldown to file while checking the results */ + try { + + /* test 1: normal, loose threshold */ + testPulldown = calculator.getHetPulldown(NORMAL_BAM_FILE, 2); + tempFile = File.createTempFile("testPulldownNormalLoose", ".txt"); + testPulldown.write(tempFile, AllelicCountTableColumns.AllelicCountTableVerbosity.FULL); + + expectedPulldown = new Pulldown(normalHeader); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 11522, 11522), 7, 4, + Nucleotide.G, Nucleotide.A, 11, 18.38)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6, + Nucleotide.G, Nucleotide.T, 14, 28.84)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 39.39)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9, + Nucleotide.T, Nucleotide.G, 15, 28.23)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5, + Nucleotide.G, Nucleotide.C, 11, 24.54)); + + Assert.assertEquals(new Pulldown(tempFile, normalHeader), expectedPulldown); + + /* test 2: normal, tight threshold */ + testPulldown = calculator.getHetPulldown(NORMAL_BAM_FILE, 12); + tempFile = File.createTempFile("testPulldownNormalTight", ".txt"); + testPulldown.write(tempFile, AllelicCountTableColumns.AllelicCountTableVerbosity.FULL); + + expectedPulldown = new Pulldown(normalHeader); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6, + Nucleotide.G, Nucleotide.T, 14, 28.84)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 39.39)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9, + Nucleotide.T, Nucleotide.G, 15, 28.23)); + + Assert.assertEquals(new Pulldown(tempFile, normalHeader), expectedPulldown); + + /* test 3: tumor, loose threshold */ + testPulldown = calculator.getHetPulldown(TUMOR_BAM_FILE, 2); + tempFile = File.createTempFile("testPulldownTumorLoose", ".txt"); + testPulldown.write(tempFile, AllelicCountTableColumns.AllelicCountTableVerbosity.FULL); + + expectedPulldown = new Pulldown(tumorHeader); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 11522, 11522), 7, 4, + Nucleotide.G, Nucleotide.A, 11, 15.63)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6, + Nucleotide.G, Nucleotide.T, 14, 24.72)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 33.89)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9, + Nucleotide.T, Nucleotide.G, 15, 24.11)); + expectedPulldown.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5, + Nucleotide.G, Nucleotide.C, 11, 21.10)); + + Assert.assertEquals(new Pulldown(tempFile, normalHeader), expectedPulldown); + + /* test 4: tumor, tight threshold */ + testPulldown = calculator.getHetPulldown(TUMOR_BAM_FILE, 12); + tempFile = File.createTempFile("testPulldownTumorTight", ".txt"); + testPulldown.write(tempFile, AllelicCountTableColumns.AllelicCountTableVerbosity.FULL); + + expectedPulldown = new Pulldown(tumorHeader); + expectedPulldown.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 33.89)); + + Assert.assertEquals(new Pulldown(tempFile, normalHeader), expectedPulldown); + + } catch (final IOException e) { + throw new UserException.CouldNotCreateOutputFile("Could not write pulldown to to file.", e); + } + + } +} diff --git a/src/test/java/org/broadinstitute/hellbender/tools/exome/GetBayesianHetCoverageIntegrationTest.java b/src/test/java/org/broadinstitute/hellbender/tools/exome/GetBayesianHetCoverageIntegrationTest.java new file mode 100644 index 00000000000..6c8d7e876b2 --- /dev/null +++ b/src/test/java/org/broadinstitute/hellbender/tools/exome/GetBayesianHetCoverageIntegrationTest.java @@ -0,0 +1,292 @@ +package org.broadinstitute.hellbender.tools.exome; + +import htsjdk.samtools.SAMFileHeader; +import htsjdk.samtools.SamReader; +import htsjdk.samtools.SamReaderFactory; +import org.broadinstitute.hellbender.CommandLineProgramTest; +import org.broadinstitute.hellbender.cmdline.ExomeStandardArgumentDefinitions; +import org.broadinstitute.hellbender.cmdline.StandardArgumentDefinitions; +import org.broadinstitute.hellbender.exceptions.UserException; +import org.broadinstitute.hellbender.utils.Nucleotide; +import org.broadinstitute.hellbender.utils.SimpleInterval; +import org.testng.Assert; +import org.testng.annotations.BeforeClass; +import org.testng.annotations.Test; + +import java.io.File; +import java.io.IOException; + +/** + * Integration test for {@link GetBayesianHetCoverage}. Uses BAM and SNP files generated from hg19mini using wgsim. + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + */ +public final class GetBayesianHetCoverageIntegrationTest extends CommandLineProgramTest { + private static final String TEST_SUB_DIR = publicTestDir + "org/broadinstitute/hellbender/tools/exome"; + + private static final File NORMAL_BAM_FILE = new File(TEST_SUB_DIR, "normal.sorted.bam"); + private static final File TUMOR_BAM_FILE = new File(TEST_SUB_DIR, "tumor.sorted.bam"); + private static final File SNP_FILE = new File(TEST_SUB_DIR, "common_SNP.interval_list"); + private static final File REF_FILE = new File(hg19MiniReference); + + private static SAMFileHeader normalHeader; + private static SAMFileHeader tumorHeader; + + @BeforeClass + public void initHeaders() throws IOException { + try (final SamReader normalBamReader = SamReaderFactory.makeDefault().open(NORMAL_BAM_FILE); + final SamReader tumorBamReader = SamReaderFactory.makeDefault().open(TUMOR_BAM_FILE)) { + normalHeader = normalBamReader.getFileHeader(); + tumorHeader = tumorBamReader.getFileHeader(); + } + } + + @Test(expectedExceptions = UserException.class) + public void testBadJobArgs_1() { + final File normalOutputFile = createTempFile("normal-test", ".tsv"); + + /* bad job: no normal BAM file */ + final String[] argumentsNoBam = { + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.NORMAL_ALLELIC_COUNTS_FILE_SHORT_NAME, normalOutputFile.getAbsolutePath() + }; + runCommandLine(argumentsNoBam); + } + + @Test(expectedExceptions = UserException.class) + public void testBadJobArgs_2() { + /* bad job: no normal het pulldown output file */ + final String[] argumentsNormalNoHetOutput = { + "-" + ExomeStandardArgumentDefinitions.NORMAL_BAM_FILE_SHORT_NAME, NORMAL_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath() + }; + runCommandLine(argumentsNormalNoHetOutput); + } + + @Test(expectedExceptions = UserException.class) + public void testBadJobArgs_3() { + /* bad job: no tumor het pulldown output file */ + final String[] argumentsTumorNoHetOutput = { + "-" + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, NORMAL_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath() + }; + runCommandLine(argumentsTumorNoHetOutput); + } + + @Test(expectedExceptions = IllegalArgumentException.class) + public void testBadPriorParameters_1() { + final File tumorOutputFile = createTempFile("tumor-test", ".tsv"); + + /* bad choice of prior parameters: max abnormal fraction > 1 */ + final String[] argumentsBadPrior = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, TUMOR_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_SHORT_NAME, tumorOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.MAXIMUM_ABNORMAL_FRACTION_SHORT_NAME, Double.toString(1.1) + }; + runCommandLine(argumentsBadPrior); + } + + @Test(expectedExceptions = IllegalArgumentException.class) + public void testBadPriorParameters_2() { + final File tumorOutputFile = createTempFile("tumor-test", ".tsv"); + + /* bad choice of prior parameters: min abnormal fraction < 0 */ + final String[] argumentsBadPrior = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, TUMOR_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_SHORT_NAME, tumorOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.MINIMUM_ABNORMAL_FRACTION_SHORT_NAME, Double.toString(-0.1) + }; + runCommandLine(argumentsBadPrior); + } + + @Test(expectedExceptions = IllegalArgumentException.class) + public void testBadPriorParameters_3() { + final File tumorOutputFile = createTempFile("tumor-test", ".tsv"); + + /* bad choice of prior parameters: max abnormal fraction < min abnormal fraction */ + final String[] argumentsBadPrior = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, TUMOR_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_SHORT_NAME, tumorOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.MINIMUM_ABNORMAL_FRACTION_SHORT_NAME, Double.toString(0.5), + "-" + GetBayesianHetCoverage.MAXIMUM_ABNORMAL_FRACTION_SHORT_NAME, Double.toString(0.4) + }; + runCommandLine(argumentsBadPrior); + } + + @Test(expectedExceptions = IllegalArgumentException.class) + public void testBadPriorParameters_4() { + final File tumorOutputFile = createTempFile("tumor-test", ".tsv"); + + /* bad choice of prior parameters: maximum copy number < 0 */ + final String[] argumentsBadPrior = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, TUMOR_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_SHORT_NAME, tumorOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.MAXIMUM_COPY_NUMBER_SHORT_NAME, Integer.toString(-1) + }; + runCommandLine(argumentsBadPrior); + } + + @Test + public void testNormalJob() { + final File normalOutputFile = createTempFile("normal-test", ".tsv"); + Pulldown normalHetPulldownExpected, normalHetPulldownResult; + + /* test 1: tight calling stringency */ + final String[] args_1 = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.NORMAL_BAM_FILE_SHORT_NAME, NORMAL_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.NORMAL_ALLELIC_COUNTS_FILE_SHORT_NAME, normalOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.READ_DEPTH_THRESHOLD_SHORT_NAME, Integer.toString(10), + "-" + GetBayesianHetCoverage.HET_CALLING_STRINGENCY_SHORT_NAME, Double.toString(15.0) + }; + runCommandLine(args_1); + + normalHetPulldownExpected = new Pulldown(normalHeader); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 39.99)); + + normalHetPulldownResult = new Pulldown(normalOutputFile, normalHeader); + + Assert.assertEquals(normalHetPulldownExpected, normalHetPulldownResult); + + /* test 2: loose calling stringency */ + final String[] args_2 = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.NORMAL_BAM_FILE_SHORT_NAME, NORMAL_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.NORMAL_ALLELIC_COUNTS_FILE_SHORT_NAME, normalOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.READ_DEPTH_THRESHOLD_SHORT_NAME, Integer.toString(10), + "-" + GetBayesianHetCoverage.HET_CALLING_STRINGENCY_SHORT_NAME, Double.toString(2.0) + }; + runCommandLine(args_2); + + normalHetPulldownExpected = new Pulldown(normalHeader); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 11522, 11522), 7, 4, + Nucleotide.G, Nucleotide.A, 11, 18.60)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6, + Nucleotide.G, Nucleotide.T, 14, 29.29)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 39.99)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9, + Nucleotide.T, Nucleotide.G, 15, 28.60)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5, + Nucleotide.G, Nucleotide.C, 11, 24.99)); + normalHetPulldownResult = new Pulldown(normalOutputFile, normalHeader); + + Assert.assertEquals(normalHetPulldownExpected, normalHetPulldownResult); + } + + @Test + public void testTumorJob() { + final File tumorOutputFile = createTempFile("tumor-test", ".tsv"); + Pulldown tumorHetPulldownExpected, tumorHetPulldownResult; + + /* test 1: tight calling stringency */ + final String[] args_1 = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, TUMOR_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_SHORT_NAME, tumorOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.READ_DEPTH_THRESHOLD_SHORT_NAME, Integer.toString(10), + "-" + GetBayesianHetCoverage.HET_CALLING_STRINGENCY_SHORT_NAME, Double.toString(10.0), + }; + runCommandLine(args_1); + + tumorHetPulldownExpected = new Pulldown(tumorHeader); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6, + Nucleotide.G, Nucleotide.T, 14, 24.85)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 34.03)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9, + Nucleotide.T, Nucleotide.G, 15, 24.23)); + + tumorHetPulldownResult = new Pulldown(tumorOutputFile, tumorHeader); + + Assert.assertEquals(tumorHetPulldownExpected, tumorHetPulldownResult); + + /* test 2: tight calling stringency */ + final String[] args_2 = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, TUMOR_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_SHORT_NAME, tumorOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.READ_DEPTH_THRESHOLD_SHORT_NAME, Integer.toString(10), + "-" + GetBayesianHetCoverage.HET_CALLING_STRINGENCY_SHORT_NAME, Double.toString(5.0) + }; + runCommandLine(args_2); + + tumorHetPulldownExpected = new Pulldown(tumorHeader); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 11522, 11522), 7, 4, + Nucleotide.G, Nucleotide.A, 11, 15.72)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6, + Nucleotide.G, Nucleotide.T, 14, 24.85)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 34.03)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9, + Nucleotide.T, Nucleotide.G, 15, 24.23)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5, + Nucleotide.G, Nucleotide.C, 11, 21.23)); + + tumorHetPulldownResult = new Pulldown(tumorOutputFile, tumorHeader); + + Assert.assertEquals(tumorHetPulldownExpected, tumorHetPulldownResult); + } + + @Test + public void testMatchedNormalTumorJob() { + final File normalOutputFile = createTempFile("normal-test", ".tsv"); + final File tumorOutputFile = createTempFile("tumor-test", ".tsv"); + Pulldown tumorHetPulldownExpected, tumorHetPulldownResult; + Pulldown normalHetPulldownExpected, normalHetPulldownResult; + + final String[] arguments = { + "-" + StandardArgumentDefinitions.REFERENCE_SHORT_NAME, REF_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.SNP_FILE_SHORT_NAME, SNP_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.NORMAL_BAM_FILE_SHORT_NAME, NORMAL_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.NORMAL_ALLELIC_COUNTS_FILE_SHORT_NAME, normalOutputFile.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_BAM_FILE_SHORT_NAME, TUMOR_BAM_FILE.getAbsolutePath(), + "-" + ExomeStandardArgumentDefinitions.TUMOR_ALLELIC_COUNTS_FILE_SHORT_NAME, tumorOutputFile.getAbsolutePath(), + "-" + GetBayesianHetCoverage.READ_DEPTH_THRESHOLD_SHORT_NAME, Integer.toString(10), + "-" + GetBayesianHetCoverage.HET_CALLING_STRINGENCY_SHORT_NAME, Double.toString(10.0) + }; + runCommandLine(arguments); + + normalHetPulldownResult = new Pulldown(normalOutputFile, normalHeader); + tumorHetPulldownResult = new Pulldown(tumorOutputFile, tumorHeader); + + normalHetPulldownExpected = new Pulldown(normalHeader); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6, + Nucleotide.G, Nucleotide.T, 14, 29.29)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17, 39.98)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9, + Nucleotide.T, Nucleotide.G, 15, 28.60)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5, + Nucleotide.G, Nucleotide.C, 11, 24.99)); + + tumorHetPulldownExpected = new Pulldown(tumorHeader); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6, + Nucleotide.G, Nucleotide.T, 14)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8, + Nucleotide.T, Nucleotide.G, 17)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9, + Nucleotide.T, Nucleotide.G, 15)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5, + Nucleotide.G, Nucleotide.C, 11)); + + Assert.assertEquals(normalHetPulldownExpected, normalHetPulldownResult); + Assert.assertEquals(tumorHetPulldownExpected, tumorHetPulldownResult); + } +} diff --git a/src/test/java/org/broadinstitute/hellbender/tools/exome/GetHetCoverageIntegrationTest.java b/src/test/java/org/broadinstitute/hellbender/tools/exome/GetHetCoverageIntegrationTest.java index 9c1eeada785..58801d39050 100644 --- a/src/test/java/org/broadinstitute/hellbender/tools/exome/GetHetCoverageIntegrationTest.java +++ b/src/test/java/org/broadinstitute/hellbender/tools/exome/GetHetCoverageIntegrationTest.java @@ -47,18 +47,18 @@ public void initHeaders() throws IOException { tumorHeader = tumorBamReader.getFileHeader(); normalHetPulldownExpected = new Pulldown(normalHeader); - normalHetPulldownExpected.add(new SimpleInterval("1", 11522, 11522), 7, 4); - normalHetPulldownExpected.add(new SimpleInterval("1", 12098, 12098), 8, 6); - normalHetPulldownExpected.add(new SimpleInterval("1", 14630, 14630), 9, 8); - normalHetPulldownExpected.add(new SimpleInterval("2", 14689, 14689), 6, 9); - normalHetPulldownExpected.add(new SimpleInterval("2", 14982, 14982), 6, 5); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 11522, 11522), 7, 4)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9)); + normalHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5)); tumorHetPulldownExpected = new Pulldown(tumorHeader); - tumorHetPulldownExpected.add(new SimpleInterval("1", 11522, 11522), 7, 4); - tumorHetPulldownExpected.add(new SimpleInterval("1", 12098, 12098), 8, 6); - tumorHetPulldownExpected.add(new SimpleInterval("1", 14630, 14630), 9, 8); - tumorHetPulldownExpected.add(new SimpleInterval("2", 14689, 14689), 6, 9); - tumorHetPulldownExpected.add(new SimpleInterval("2", 14982, 14982), 6, 5); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 11522, 11522), 7, 4)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9)); + tumorHetPulldownExpected.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5)); } } diff --git a/src/test/java/org/broadinstitute/hellbender/tools/exome/HetPulldownCalculatorUnitTest.java b/src/test/java/org/broadinstitute/hellbender/tools/exome/HetPulldownCalculatorUnitTest.java index a60e4f8683f..3948ebfd7e9 100644 --- a/src/test/java/org/broadinstitute/hellbender/tools/exome/HetPulldownCalculatorUnitTest.java +++ b/src/test/java/org/broadinstitute/hellbender/tools/exome/HetPulldownCalculatorUnitTest.java @@ -137,16 +137,16 @@ public void testIsPileupHetCompatible(final Nucleotide.Counter baseCounts, final @DataProvider(name = "inputGetNormalHetPulldown") public Object[][] inputGetNormalHetPulldown() { final Pulldown normalHetPulldown1 = new Pulldown(normalHeader); - normalHetPulldown1.add(new SimpleInterval("1", 11522, 11522), 7, 4); - normalHetPulldown1.add(new SimpleInterval("1", 12098, 12098), 8, 6); - normalHetPulldown1.add(new SimpleInterval("1", 14630, 14630), 9, 8); - normalHetPulldown1.add(new SimpleInterval("2", 14689, 14689), 6, 9); - normalHetPulldown1.add(new SimpleInterval("2", 14982, 14982), 6, 5); + normalHetPulldown1.add(new AllelicCount(new SimpleInterval("1", 11522, 11522), 7, 4)); + normalHetPulldown1.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6)); + normalHetPulldown1.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8)); + normalHetPulldown1.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9)); + normalHetPulldown1.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5)); //changing pValThreshold from 0.05 -> 0.95 only keeps hets close to balanced final Pulldown normalHetPulldown2 = new Pulldown(normalHeader); - normalHetPulldown2.add(new SimpleInterval("1", 14630, 14630), 9, 8); - normalHetPulldown2.add(new SimpleInterval("2", 14982, 14982), 6, 5); + normalHetPulldown2.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8)); + normalHetPulldown2.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5)); return new Object[][]{ {0.05, normalHetPulldown1}, @@ -173,11 +173,11 @@ public void testBadpValue() { @DataProvider(name = "inputGetTumorHetPulldown") public Object[][] inputGetTumorHetPulldown() { final Pulldown tumorHetPulldown = new Pulldown(normalHeader); - tumorHetPulldown.add(new SimpleInterval("1", 11522, 11522), 7, 4); - tumorHetPulldown.add(new SimpleInterval("1", 12098, 12098), 8, 6); - tumorHetPulldown.add(new SimpleInterval("1", 14630, 14630), 9, 8); - tumorHetPulldown.add(new SimpleInterval("2", 14689, 14689), 6, 9); - tumorHetPulldown.add(new SimpleInterval("2", 14982, 14982), 6, 5); + tumorHetPulldown.add(new AllelicCount(new SimpleInterval("1", 11522, 11522), 7, 4)); + tumorHetPulldown.add(new AllelicCount(new SimpleInterval("1", 12098, 12098), 8, 6)); + tumorHetPulldown.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8)); + tumorHetPulldown.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9)); + tumorHetPulldown.add(new AllelicCount(new SimpleInterval("2", 14982, 14982), 6, 5)); final IntervalList normalHetIntervals = new IntervalList(tumorHeader); normalHetIntervals.add(new Interval("1", 11522, 11522)); @@ -194,8 +194,8 @@ public Object[][] inputGetTumorHetPulldown() { @DataProvider(name = "inputGetTumorHetPulldownMin15") public Object[][] inputGetTumorHetPulldown15() { final Pulldown tumorHetPulldown = new Pulldown(normalHeader); - tumorHetPulldown.add(new SimpleInterval("1", 14630, 14630), 9, 8); - tumorHetPulldown.add(new SimpleInterval("2", 14689, 14689), 6, 9); + tumorHetPulldown.add(new AllelicCount(new SimpleInterval("1", 14630, 14630), 9, 8)); + tumorHetPulldown.add(new AllelicCount(new SimpleInterval("2", 14689, 14689), 6, 9)); final IntervalList normalHetIntervals = new IntervalList(tumorHeader); normalHetIntervals.add(new Interval("1", 14630, 14630)); diff --git a/src/test/java/org/broadinstitute/hellbender/tools/exome/HeterogeneousHeterozygousPileupPriorModelUnitTest.java b/src/test/java/org/broadinstitute/hellbender/tools/exome/HeterogeneousHeterozygousPileupPriorModelUnitTest.java new file mode 100644 index 00000000000..fe06f84177c --- /dev/null +++ b/src/test/java/org/broadinstitute/hellbender/tools/exome/HeterogeneousHeterozygousPileupPriorModelUnitTest.java @@ -0,0 +1,49 @@ +package org.broadinstitute.hellbender.tools.exome; + +import org.broadinstitute.hellbender.utils.test.BaseTest; +import org.junit.Before; +import org.testng.Assert; +import org.testng.annotations.BeforeClass; +import org.testng.annotations.Test; + +import java.util.stream.IntStream; + +/** + * Unit tests for {@link HeterogeneousHeterozygousPileupPriorModel}. + * + * @author Mehrtash Babadi <mehrtash@broadinstitute.org> + */ +public final class HeterogeneousHeterozygousPileupPriorModelUnitTest extends BaseTest { + + private static final double MIN_ABNORMAL_FRACTION = 0.1; + private static final double MAX_ABNORMAL_FRACTION = 0.9; + private static final int MAX_COPY_NUMBER = 4; + private static final int QUADRATURE_ORDER = 300; + + private static HeterogeneousHeterozygousPileupPriorModel hetPrior; + + @BeforeClass + public void initPrior() { + hetPrior = new HeterogeneousHeterozygousPileupPriorModel(MIN_ABNORMAL_FRACTION, MAX_ABNORMAL_FRACTION, + MAX_COPY_NUMBER, QUADRATURE_ORDER); + } + + @Test + public void testQuadrature() { + double sumWeights = hetPrior.gaussIntegrationWeights.stream().mapToDouble(Double::doubleValue).sum(); + double minHetAlleleFraction = (1 - MAX_ABNORMAL_FRACTION) / (MAX_COPY_NUMBER * MAX_ABNORMAL_FRACTION + + 2 * (1 - MAX_ABNORMAL_FRACTION)); + Assert.assertEquals(sumWeights, 1 - 2 * minHetAlleleFraction, 1e-8); + Assert.assertEquals(hetPrior.gaussIntegrationAbscissas.size(), QUADRATURE_ORDER); + } + + @Test + public void testAlelleRatioPrior() { + /* the prior should integrate to 1 */ + Assert.assertEquals(IntStream.range(0, hetPrior.gaussIntegrationAbscissas.size()) + .mapToDouble(i -> hetPrior.gaussIntegrationWeights.get(i) * hetPrior.alleleFractionPriors.get(i)) + .sum(), 1.0, 1e-3); + hetPrior.alleleFractionPriors.stream().forEach(x -> Assert.assertTrue(x > 0)); + } + +} diff --git a/src/test/java/org/broadinstitute/hellbender/utils/GATKProtectedMathUtilsTest.java b/src/test/java/org/broadinstitute/hellbender/utils/GATKProtectedMathUtilsTest.java index a43eb994c04..58eca44a418 100644 --- a/src/test/java/org/broadinstitute/hellbender/utils/GATKProtectedMathUtilsTest.java +++ b/src/test/java/org/broadinstitute/hellbender/utils/GATKProtectedMathUtilsTest.java @@ -16,7 +16,7 @@ public void naturalLogSumNaturalLogTest() { final double[] logSpaceValues= Arrays.stream(realSpaceValues).map(Math::log).toArray(); final double expected = Math.log(Arrays.stream(realSpaceValues).sum()); - final double actual = GATKProtectedMathUtils.naturalLogSumExp(logSpaceValues); + final double actual = GATKProtectedMathUtils.logSumExp(logSpaceValues); Assert.assertEquals(actual, expected, 1e-10); } diff --git a/src/test/java/org/broadinstitute/hellbender/utils/hmm/TestHMModel.java b/src/test/java/org/broadinstitute/hellbender/utils/hmm/TestHMModel.java index 22b747544e9..9cd75a29bb4 100644 --- a/src/test/java/org/broadinstitute/hellbender/utils/hmm/TestHMModel.java +++ b/src/test/java/org/broadinstitute/hellbender/utils/hmm/TestHMModel.java @@ -37,17 +37,17 @@ static TestHMModel fromPhredProbabilities(final double ... phred) { final DoubleUnaryOperator phredToLog = d -> d * -.1 * LN_OF_10; final double[] logPriorsRaw = DoubleStream.of(priors).map(phredToLog).toArray(); - final double logPriorsSum = GATKProtectedMathUtils.naturalLogSumExp(logPriorsRaw); + final double logPriorsSum = GATKProtectedMathUtils.logSumExp(logPriorsRaw); final double[] logPriors = DoubleStream.of(logPriorsRaw).map(d -> d - logPriorsSum).toArray(); final double[][] logEmissionProbs = Stream.of(emission) .map(x -> { final double[] result = DoubleStream.of(x).map(phredToLog).toArray(); - final double sum = GATKProtectedMathUtils.naturalLogSumExp(result); + final double sum = GATKProtectedMathUtils.logSumExp(result); return DoubleStream.of(result).map(d -> d - sum).toArray(); }) .toArray(double[][]::new); final double[][] logTransitionProbs = Stream.of(transition) .map(x -> { final double[] result = DoubleStream.of(x).map(phredToLog).toArray(); - final double sum = GATKProtectedMathUtils.naturalLogSumExp(result); + final double sum = GATKProtectedMathUtils.logSumExp(result); return DoubleStream.of(result).map(d -> d - sum).toArray(); }) .toArray(double[][]::new); return new TestHMModel(logPriors, logEmissionProbs, logTransitionProbs); @@ -185,7 +185,7 @@ private State generateNextState(final State previousState, final Integer previou for (int i = 0; i < logTransitionProbs.length; i++) { logTransitionProbs[i] = logTransitionProbability(previousState, previousPosition, State.values()[i], nextPosition); } - final double total = Math.exp(GATKProtectedMathUtils.naturalLogSumExp(logTransitionProbs)); + final double total = Math.exp(GATKProtectedMathUtils.logSumExp(logTransitionProbs)); final double uniform = rdn.nextDouble() * total; double accumulative = 0; for (int i = 0; i < logTransitionProbs.length; i++) { @@ -202,7 +202,7 @@ private Datum generateDatum(final State state, final Integer position, final Ran for (int i = 0; i < logEmissionProbs.length; i++) { logEmissionProbs[i] = logEmissionProbability(Datum.values()[i], state, position); } - final double total = Math.exp(GATKProtectedMathUtils.naturalLogSumExp(logEmissionProbs)); + final double total = Math.exp(GATKProtectedMathUtils.logSumExp(logEmissionProbs)); final double uniform = rdn.nextDouble() * total; double accumulate = 0; @@ -216,7 +216,7 @@ private Datum generateDatum(final State state, final Integer position, final Ran } private State generateFirstState(final Integer firstPosition, final Random rdn) { - final double uniform = rdn.nextDouble() * Math.exp(GATKProtectedMathUtils.naturalLogSumExp(priors)); + final double uniform = rdn.nextDouble() * Math.exp(GATKProtectedMathUtils.logSumExp(priors)); double accumulative = 0; for (int i = 0; i < priors.length; i++) { accumulative += Math.exp(logPriorProbability(State.values()[i], firstPosition)); diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-pon-bad.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-pon-bad.tsv index 7604b781351..a0f427754a1 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-pon-bad.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-pon-bad.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT NUM_SAMPLES +CONTIG POSITION REF_COUNT ALT_COUNT NUM_SAMPLES 1 1 1306 1191 49 1 2 1279 1248 50 1 3 1250 1259 50 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-pon-normal.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-pon-normal.tsv index dac710f8a86..23353cb61a5 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-pon-normal.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-pon-normal.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT NUM_SAMPLES +CONTIG POSITION REF_COUNT ALT_COUNT NUM_SAMPLES 1 1 1317 1218 50 1 2 1304 1246 50 1 3 1287 1168 50 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-bad.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-bad.tsv index 85f5b52cc5e..a6dec700252 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-bad.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-bad.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT +CONTIG POSITION REF_COUNT ALT_COUNT 1 1 25 22 1 2 25 27 1 3 23 26 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-event.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-event.tsv index af79ad13c11..a09a8612a61 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-event.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-event.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT +CONTIG POSITION REF_COUNT ALT_COUNT 1 1 24 22 1 2 27 23 1 3 33 21 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-normal.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-normal.tsv index 5e6e44e3cda..186ca00fa01 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-normal.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/allelic-pon-test-sample-normal.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT +CONTIG POSITION REF_COUNT ALT_COUNT 1 1 20 21 1 2 26 15 1 3 22 31 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-basic.tsv similarity index 61% rename from src/test/resources/org/broadinstitute/hellbender/tools/exome/snps.tsv rename to src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-basic.tsv index 4b1f748f0c2..26ea64877ec 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-basic.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT +CONTIG POSITION REF_COUNT ALT_COUNT 1 881918 14 21 1 909238 13 11 1 934940 14 0 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-acnv-modeller.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-acnv-modeller.tsv index 89aaae696fe..d5d4b6abe56 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-acnv-modeller.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-acnv-modeller.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT +CONTIG POSITION REF_COUNT ALT_COUNT 1 1 28 8 1 13 30 8 1 25 33 9 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-allelic-integration.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-allelic-integration.tsv index 9b75a21d1cf..d4da569cdc9 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-allelic-integration.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-allelic-integration.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT +CONTIG POSITION REF_COUNT ALT_COUNT 1 881918 14 21 1 909238 13 11 1 934940 14 0 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-small-segment-merging-base.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-small-segment-merging-base.tsv index be00e717a94..00c0c3ea857 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-small-segment-merging-base.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-for-small-segment-merging-base.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT +CONTIG POSITION REF_COUNT ALT_COUNT 1 154 120 17 1 199 64 33 1 226 8 36 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-full.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-full.tsv new file mode 100644 index 00000000000..2bac94ce0ec --- /dev/null +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-full.tsv @@ -0,0 +1,5 @@ +CONTIG POSITION REF_COUNT ALT_COUNT REF_NUCLEOTIDE ALT_NUCLEOTIDE READ_DEPTH HET_LOG_ODDS +1 881918 14 21 A C 35 12.0 +1 909238 13 11 T G 26 120.5 +1 934940 14 0 A G 17 -16.1 +1 949608 20 14 G T 34 54.3 \ No newline at end of file diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-intermediate.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-intermediate.tsv new file mode 100644 index 00000000000..37994f43eb8 --- /dev/null +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-intermediate.tsv @@ -0,0 +1,5 @@ +CONTIG POSITION REF_COUNT ALT_COUNT REF_NUCLEOTIDE ALT_NUCLEOTIDE READ_DEPTH +1 881918 14 21 A C 35 +1 909238 13 11 T G 26 +1 934940 14 0 A G 17 +1 949608 20 14 G T 34 \ No newline at end of file diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-simplified-for-allelic-fraction-segmentation.tsv b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-simplified-for-allelic-fraction-segmentation.tsv index 9952b38f13e..377dc60a283 100644 --- a/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-simplified-for-allelic-fraction-segmentation.tsv +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/snps-simplified-for-allelic-fraction-segmentation.tsv @@ -1,4 +1,4 @@ -CONTIG POS REF_COUNT ALT_COUNT +CONTIG POSITION REF_COUNT ALT_COUNT 1 212360 80 20 1 241501 80 20 1 242173 80 20 diff --git a/src/test/resources/org/broadinstitute/hellbender/tools/exome/test_fake_generated_pileup.txt b/src/test/resources/org/broadinstitute/hellbender/tools/exome/test_fake_generated_pileup.txt new file mode 100644 index 00000000000..d63c9c02ee0 --- /dev/null +++ b/src/test/resources/org/broadinstitute/hellbender/tools/exome/test_fake_generated_pileup.txt @@ -0,0 +1,60 @@ +A: 0.0929,0.0645,0.0302,0.0541,0.1152,0.1014,0.1069 +C: 0.1057 +T: 0.0741,0.1151,0.0657,0.1116,0.1044,0.1384,0.1164,0.1884,0.1066 +G: +het_likelihood: -16.01225353142163 +hom_likelihood: -31.007832859742628 +A: 0.1156,0.1276,0.1068,0.1066,0.0942,0.1476 +C: 0.0873 +T: 0.1003,0.0808,0.1251,0.1074,0.1164,0.0898,0.0607,0.0865,0.0935,0.1193,0.1376 +G: 0.1297 +het_likelihood: -19.757613024346206 +hom_likelihood: -28.111845056457867 +A: 0.1115,0.167,0.059,0.1174,0.0965,0.1543 +C: 0.119,0.0783,0.0981,0.1008 +T: 0.1139,0.0399,0.0886,0.1184,0.1002 +G: 0.1164 +het_likelihood: -25.77581422770733 +hom_likelihood: -35.967868122777325 +A: 0.1354,0.0715 +C: +T: +G: +het_likelihood: -1.4312167158461966 +hom_likelihood: -0.9114829948415626 +A: 0.0683,0.1015 +C: 0.1019 +T: 0.129,0.0957 +G: +het_likelihood: -6.629048950882817 +hom_likelihood: -10.420790594024472 +A: 0.1418 +C: +T: 0.1163,0.0519,0.1079,0.0894,0.081,0.1043,0.0982,0.1447,0.0883,0.0749,0.1068,0.1065,0.0884,0.0806,0.095 +G: 0.1056 +het_likelihood: -11.574501333892508 +hom_likelihood: -8.603112076541102 +A: +C: +T: 0.1093,0.0003,0.0201,0.1198 +G: 0.1 +het_likelihood: -5.820671634440884 +hom_likelihood: -4.358298802200576 +A: +C: +T: 0.1011,0.0821,0.0801,0.1452,0.1252,0.1276,0.0747,0.1138 +G: +het_likelihood: -4.352045143460826 +hom_likelihood: -1.5944994015660068 +A: 0.0818,0.084,0.1051,0.0992,0.0676,0.0859,0.1056,0.107,0.0636,0.0796,0.1333,0.0703 +C: +T: 0.1322 +G: +het_likelihood: -7.160920445716858 +hom_likelihood: -4.952992050239895 +A: 0.0699,0.1046,0.0903,0.1062,0.1695,0.0898,0.1166,0.0507 +C: +T: +G: 0.1111 +het_likelihood: -7.5992982204660215 +hom_likelihood: -4.834771387355668