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GERMLINE_SNV_ANNOT_README.md

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Kids First DRC Germline SNV Annotation Workflow

This workflow is used to annotate germline outputs with popular annotation resources. This includes using VEP to annotate with ENSEMBL v105 reference as well using bcftools to add further annotation described below.

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Overall annotation steps

  1. Prefilter input VCF (optional) to remove variants that are undesired to go into annotation
  2. Normalize VCF
  3. Strip pre-existing annotations (optional) to prevent downstream conflicts
  4. Annotate with VEP 105. Optional plugins include:
    • dbnsfp
    • cadd
  5. Use echtvar to annotate with an external reference (default gnomad 3.1.1)
  6. Use bcftools to annotate with another external reference (optional clinvar)
  7. Simple rename outputs step

Default annotations

By default, the workflow will add the following annotations:

ENSEMBL 105

This is added on using variant effect predictor to use the ENSEMBL reference to add gene model information as well as additional resources provided in their cache. It's highly recommended that when you download their cache, to convert and index. It will speed up annotation and reduce memory footprint significantly. Annotation resources in the cache include:

# CACHE UPDATED 2022-09-26 18:18:29
assembly	GRCh38
bam	GCF_000001405.39_GRCh38.p13_knownrefseq_alns.bam
polyphen	b
sift	b
source_assembly	GRCh38.p13
source_gencode	GENCODE 39
source_genebuild	2014-07
source_polyphen	2.2.2
source_refseq	2021-05-28 21:42:08 - GCF_000001405.39_GRCh38.p13_genomic.gff
source_sift	sift5.2.2
species	homo_sapiens
variation_cols	chr,variation_name,failed,somatic,start,end,allele_string,strand,minor_allele,minor_allele_freq,clin_sig,phenotype_or_disease,clin_sig_allele,pubmed,var_synonyms,AFR,AMR,EAS,EUR,SAS,AA,EA,gnomAD,gnomAD_AFR,gnomAD_AMR,gnomAD_ASJ,gnomAD_EAS,gnomAD_FIN,gnomAD_NFE,gnomAD_OTH,gnomAD_SAS
source_COSMIC	94
source_HGMD-PUBLIC	20204
source_ClinVar	105202106
source_dbSNP	154
source_1000genomes	phase3
source_ESP	V2-SSA137
source_gnomAD	r2.1.1
regulatory	1
cell_types	A549,A673,B,B_(PB),CD14+_monocyte_(PB),CD14+_monocyte_1,CD4+_CD25+_ab_Treg_(PB),CD4+_ab_T,CD4+_ab_T_(PB)_1,CD4+_ab_T_(PB)_2,CD4+_ab_T_(Th),CD4+_ab_T_(VB),CD8+_ab_T_(CB),CD8+_ab_T_(PB),CMP_CD4+_1,CMP_CD4+_2,CMP_CD4+_3,CM_CD4+_ab_T_(VB),DND-41,EB_(CB),EM_CD4+_ab_T_(PB),EM_CD8+_ab_T_(VB),EPC_(VB),GM12878,H1-hESC_2,H1-hESC_3,H9_1,HCT116,HSMM,HUES48,HUES6,HUES64,HUVEC,HUVEC-prol_(CB),HeLa-S3,HepG2,K562,M0_(CB),M0_(VB),M1_(CB),M1_(VB),M2_(CB),M2_(VB),MCF-7,MM.1S,MSC,MSC_(VB),NHLF,NK_(PB),NPC_1,NPC_2,NPC_3,PC-3,PC-9,SK-N.,T_(PB),Th17,UCSF-4,adrenal_gland,aorta,astrocyte,bipolar_neuron,brain_1,cardiac_muscle,dermal_fibroblast,endodermal,eosinophil_(VB),esophagus,foreskin_fibroblast_2,foreskin_keratinocyte_1,foreskin_keratinocyte_2,foreskin_melanocyte_1,foreskin_melanocyte_2,germinal_matrix,heart,hepatocyte,iPS-15b,iPS-20b,iPS_DF_19.11,iPS_DF_6.9,keratinocyte,kidney,large_intestine,left_ventricle,leg_muscle,lung_1,lung_2,mammary_epithelial_1,mammary_epithelial_2,mammary_myoepithelial,monocyte_(CB),monocyte_(VB),mononuclear_(PB),myotube,naive_B_(VB),neuron,neurosphere_(C),neurosphere_(GE),neutro_myelocyte,neutrophil_(CB),neutrophil_(VB),osteoblast,ovary,pancreas,placenta,psoas_muscle,right_atrium,right_ventricle,sigmoid_colon,small_intestine_1,small_intestine_2,spleen,stomach_1,stomach_2,thymus_1,thymus_2,trophoblast,trunk_muscle
source_regbuild	1.0
var_type	tabix

gnomAD 3.1.1

Using echtvar, we annotate from a custom implementation of gnomAD v3.1.1 the following population statistics (columns are give a gnomad_3_1_1_ prefix to denote source):

gnomad_3_1_1_AC
gnomad_3_1_1_AN
gnomad_3_1_1_AF
gnomad_3_1_1_nhomalt
gnomad_3_1_1_AC_popmax
gnomad_3_1_1_AN_popmax
gnomad_3_1_1_AF_popmax
gnomad_3_1_1_nhomalt_popmax
gnomad_3_1_1_AC_controls_and_biobanks
gnomad_3_1_1_AN_controls_and_biobanks
gnomad_3_1_1_AF_controls_and_biobanks
gnomad_3_1_1_AF_non_cancer
gnomad_3_1_1_primate_ai_score
gnomad_3_1_1_splice_ai_consequence
gnomad_3_1_1_AF_non_cancer_afr
gnomad_3_1_1_AF_non_cancer_ami
gnomad_3_1_1_AF_non_cancer_asj
gnomad_3_1_1_AF_non_cancer_eas
gnomad_3_1_1_AF_non_cancer_fin
gnomad_3_1_1_AF_non_cancer_mid
gnomad_3_1_1_AF_non_cancer_nfe
gnomad_3_1_1_AF_non_cancer_oth
gnomad_3_1_1_AF_non_cancer_raw
gnomad_3_1_1_AF_non_cancer_sas
gnomad_3_1_1_AF_non_cancer_amr
gnomad_3_1_1_AF_non_cancer_popmax
gnomad_3_1_1_AF_non_cancer_all_popmax
gnomad_3_1_1_FILTER

Optional annotations

dbNSFP v4.3a

This resource compiles from dozens of sources annotations for ~84M SNVs. By default, from this resource, we recommend the following:

SIFT4G_pred
Polyphen2_HDIV_pred
Polyphen2_HVAR_pred
LRT_pred
MutationTaster_pred
MutationAssessor_pred
FATHMM_pred
PROVEAN_pred
VEST4_score
VEST4_rankscore
MetaSVM_pred
MetaLR_pred
MetaRNN_pred
M-CAP_pred
REVEL_score
REVEL_rankscore
PrimateAI_pred
DEOGEN2_pred
BayesDel_noAF_pred
ClinPred_pred
LIST-S2_pred
Aloft_pred
fathmm-MKL_coding_pred
fathmm-XF_coding_pred
Eigen-phred_coding
Eigen-PC-phred_coding
phyloP100way_vertebrate
phyloP100way_vertebrate_rankscore
phastCons100way_vertebrate
phastCons100way_vertebrate_rankscore
TWINSUK_AC
TWINSUK_AF
ALSPAC_AC
ALSPAC_AF
UK10K_AC
UK10K_AF
gnomAD_exomes_controls_AC
gnomAD_exomes_controls_AN
gnomAD_exomes_controls_AF
gnomAD_exomes_controls_nhomalt
gnomAD_exomes_controls_POPMAX_AC
gnomAD_exomes_controls_POPMAX_AN
gnomAD_exomes_controls_POPMAX_AF
gnomAD_exomes_controls_POPMAX_nhomalt
Interpro_domain
GTEx_V8_gene
GTEx_V8_tissue

CADD v1.6

Using a VEP plugin, we add Combined Annotation Dependent Depletion scores

ClinVar 20220507

A curated resource with annotations of clinical significance per variant. Note, for this pipeline, the default reference was modified by:

  • Switching from 1 chromosome nomenclature to chr1, and especially MT -> chrM
  • Removing the entry assigned to NW_009646201.1. It's a benign it and also not present in our fasta reference. We recommend the following:
ALLELEID
CLNDN
CLNDNINCL
CLNDISDB
CLNDISDBINCL
CLNHGVS
CLNREVSTAT
CLNSIG
CLNSIGCONF
CLNSIGINCL
CLNVC
CLNVCSO
CLNVI

InterVar

This is a custom reference generated by the authors of the tool linked above. It contains only exonic snps. To utilize the full capabilities of their classification, you must run the tool.

Workflow Inputs

Required

  • indexed_reference_fasta files: Homo_sapiens_assembly38.fasta, Homo_sapiens_assembly38.dict, Homo_sapiens_assembly38.fasta.fai
  • input_vcf: Input vcf file to annotate
  • output_basename: string prefix of outputs
  • tool_name: short descriptive string of tool output being annotated

RECOMMENDED

  • echtvar_anno_zips file array: Annotation ZIP files for echtvar anno
  • vep_cache file: homo_sapiens_merged_vep_105_indexed_GRCh38.tar.gz
  • merged boolean: Set to true if merged cache used, default: true
  • run_cache_existing boolean: Run the check_existing flag for cache, default: true
  • run_cache_af boolean: Run the allele frequency flags for cache, default: true
  • run_stats boolean: Create stats file. Disable for speed, default: false

Optional

  • bcftools_prefilter_csv: CSV of bcftools filter params if you want to prefilter before annotation
  • disable_normalization boolean: Skip normalizing if input is already normed, default is false
  • bcftools_strip_columns: CSV string of columns to strip if needed to avoid conflict, i.e INFO/AF
  • vep_ram int: In GB, may need to increase this value depending on the size/complexity of input, default: 48
  • vep_cores int: Number of cores to use. May need to increase for really large inputs, default: 32,
  • vep_buffer_size int: Increase or decrease to balance speed and memory usage, default: 100000
  • bcftools_annot_clinvar_columns: CSV string of columns from annotation to port into the input VCF, default: INFO/ALLELEID,INFO/CLNDN,INFO/CLNDNINCL,INFO/CLNDISDB,INFO/CLNDISDBINCL,INFO/CLNHGVS,INFO/CLNREVSTAT,INFO/CLNSIG,INFO/CLNSIGCONF,INFO/CLNSIGINCL,INFO/CLNVC,INFO/CLNVCSO,INFO/CLNVI
  • clinvar_annotation_vcf files: clinvar_20220507_chr_fixed.vcf.gz, clinvar_20220507_chr_fixed.vcf.gz.tbi
  • dbnsfp file: dbNSFP4.3a_grch38.gz, dbNSFP4.3a_grch38.gz.tbi, dbNSFP4.3a_grch38.readme.txt
  • dbnsfp_fields string: CSV string with desired fields to annotate. Use ALL to grab all, default: SIFT4G_pred,Polyphen2_HDIV_pred,Polyphen2_HVAR_pred,LRT_pred,MutationTaster_pred,MutationAssessor_pred,FATHMM_pred,PROVEAN_pred,VEST4_score,VEST4_rankscore,MetaSVM_pred,MetaLR_pred,MetaRNN_pred,M-CAP_pred,REVEL_score,REVEL_rankscore,PrimateAI_pred,DEOGEN2_pred,BayesDel_noAF_pred,ClinPred_pred,LIST-S2_pred,Aloft_pred,fathmm-MKL_coding_pred,fathmm-XF_coding_pred,Eigen-phred_coding,Eigen-PC-phred_coding,phyloP100way_vertebrate,phyloP100way_vertebrate_rankscore,phastCons100way_vertebrate,phastCons100way_vertebrate_rankscore,TWINSUK_AC,TWINSUK_AF,ALSPAC_AC,ALSPAC_AF,UK10K_AC,UK10K_AF,gnomAD_exomes_controls_AC,gnomAD_exomes_controls_AN,gnomAD_exomes_controls_AF,gnomAD_exomes_controls_nhomalt,gnomAD_exomes_controls_POPMAX_AC,gnomAD_exomes_controls_POPMAX_AN,gnomAD_exomes_controls_POPMAX_AF,gnomAD_exomes_controls_POPMAX_nhomalt,Interpro_domain,GTEx_V8_gene,GTEx_V8_tissue
  • cadd_indels file: CADDv1.6-38-gnomad.genomes.r3.0.indel.tsv.gz, CADDv1.6-38-gnomad.genomes.r3.0.indel.tsv.gz.tbi
  • cadd_snvs file: CADDv1.6-38-whole_genome_SNVs.tsv.gz, CADDv1.6-38-whole_genome_SNVs.tsv.gz.tbi
  • intervar file: Exons.all.hg38.intervar.2021-07-31.vcf.gz, Exons.all.hg38.intervar.2021-07-31.vcf.gz.tbi

Workflow Outputs

  • annotated_vcf file: VCF file with all applied annotations

Notes On Reference Generation

Currently, VEP not only provides gene model annotation, but also allows for additional annotations to be added. Therefore, for CADD and dbNSFP, existing files were formatted in order to use VEP plugins. Please see their documentation for information on how the references were generated.