Parsnp is a command-line-tool for efficient microbial core genome alignment and SNP detection. Parsnp was designed to work in tandem with Gingr, a flexible platform for visualizing genome alignments and phylogenetic trees; both Parsnp and Gingr form part of the Harvest suite :
Parsnp is available on Bioconda. This is the recommended method of installation.
Once you have added the Bioconda channel to your conda environment, parsnp can be installed via
conda install -c bioconda parsnp
Instructions for building Parsnp from source are available towards the end of this README.
Parsnp can be run multiple ways, but the most common is with a set of genomes and a reference.
parsnp -g <reference_genbank> -d <genomes>
parsnp -r <reference_fasta> -d <genomes>
For example,
parsnp -r examples/mers_virus/ref/England1.fna -d examples/mers_virus/genomes/*.fna -o examples-out
Parsnp 2 will group query genomes up into random partitions of at least --min-partition-size genomes each (50 by default). Parsnp is then run independently on each group, and the resulting alignment of each group is merged into a single alignment of all input genomes. This limits the input size for an individual "core" Parsnp step, leading to significantly less memory and CPU usage. We've also shown, on simulated and empirical data, that this partitioning step often leads to increased core-genome size and better phylogenetic signal.
The --no-partition flag allows users to run all query genomes at once.
parsnp.xmfais the core-genome alignment.parsnp.ggris the compressed representation of the alignment generated by the harvest-toolkit. This file can be used to visualize alignments with Gingr.parsnp.snps.mblocksis the core-SNP signature of each sequence in fasta format. This is the file which is used to generateparsnp.treeparsnp.treeis the resulting phylogeny.- If run in partition mode, Parsnp will produce a
partitionfolder in the output directory, which contains the output of each of the partitioned runs.
The output XMFA file contains a header section mapping contig names to indices. Following the header section, the LCBs/clusters are reported in the XMFA format, where the ID for each record in an LCB is formatted as:
[fileidx]:[concat_start]-[concat_end] [strand] cluster[x] s[contig_idx]:p[contig_pos]
The concat_start and concat_end values are internal to parsnp. The sequence for this record can be found in the file at index fileidx (these are declared at the top of the xmfa) on the contig_idxth contig starting at position contig_pos.
To build Parsnp from source, users must have automake 1.15, autoconf, and libtool installed. Parsnp also requires RaxML (or FastTree), Harvest-tools, biopython, tqdm, and numpy. Some additional features require pySPOA, Mash, FastANI, and Phipack. All of these packages are available via Conda (many on the Bioconda channel).
First, you must build the Muscle library
cd muscle
./autogen.sh
./configure --prefix=$PWD CXXFLAGS='-fopenmp'
make install
Now we can build Parsnp
cd ..
./autogen.sh
./configure
make LDADD=-lMUSCLE-3.7
make install
If you wish to be able to move your Parsnp installation around after building, build the parsp binary as follows (after building the Muscle library)
./autogen.sh
export ORIGIN=\$ORIGIN
./configure LDFLAGS='-Wl,-rpath,$$ORIGIN/../muscle/lib'
make LDADD=-lMUSCLE-3.7
make install
Note that the parsnp executable in bin/ is not the same as the one in the root level. The former is an alias for Parsnp.py while the latter is the core algorithm of Parsnp that we build above.
Recent OSX have a Gatekeeper, that's designed to ensure that only softwre from known developers runs on tour Mac. Please refer to this link to enable the binaries shipped with Parsnp to run: https://support.apple.com/en-us/HT202491
CITATION provides details on how to cite Parsnp.
LICENSE provides licensing information.
- The Harvest project page provides examples of how to use Gingr and HarvestTools with Parsnp, however the Parsnp examples are not up-to-date with the current interface.
