Code Monkey home page Code Monkey logo

vcf-melt's Introduction

vcf-melt

This repo is based on the vcf_melt script from PyVCF. It has been expanded upon to support snpEff-annotated vcf files.

The 'melt' in vcf-melt refers to the process of 'melting' a wide dataset into a long dataset, as is commonly done when preparing Tidy data. A similar procedure is provided by the melt function in the popular pandas python library.

This tool does not completely 'melt' its input, but does resolve several issues with one-to-many relationships that arise when coverting vcf files to csv format:

  • Each variant for each sample is reported on a separate line.
  • Each annotation for each variant is reported on a separate line.
  • In cases where there are multiple alternate alleles for a variant, each alternate allele is reported on a separate line.

Dependencies

The vcf_melt.py script depends on PyVCF. Dependencies are listed in the setup.py file.

Note that PyVCF is not compatible with Python > 3.5. A future version of this script may switch to either manually parsing the vcf contents using only python standard library features, or switching to using cyvcf2 to parse the input.

Usage

usage: vcf-melt [-h] vcf

positional arguments:
  vcf

optional arguments:
  -h, --help  show this help message and exit

The vcf-melt script takes a vcf file as input and prints the 'melted' csv-formatted output to stdandard output. Eg:

vcf-melt a_vcf_file.vcf > melted_vcf.csv

Output

Output is in .csv format.

The first field is the sample ID:

Header Description
SAMPLE Sample identifier

The following 7 fields correspond to 7 of the 8 fixed mandatory columns as defined in the VCF spec:

Header Description
CHROM Chromosome (or contig) on which the variant occurs
POS Position of the variant, relative to the reference sequence
ID An identifier for the variant, or . if no identifier is available
REF Reference base(s)
ALT Alternate base(s)
QUAL Phred-scaled quality score for the evidence of the alternate allele
FILTER PASS if the variant passed all quality filters, or . if no filters have been applied

Refer to the VCF spec for more detailed descriptions of these fields.

The eighth mandatory column (INFO) is split out into separate fields, according to the INFO fields present in the file. These fields may vary depending on the tool(s) used to produce the .vcf file. Some examples:

Header Description
NS Number of samples with data
DP Total read depth at the locus
DPB Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype
AC Total number of alternate alleles in called genotypes
AN Total number of alleles in called genotypes
AF Estimated allele frequency

All INFO fields are prefixed with INFO_ in the output .csv file.

If the .vcf file includes annotation information, the ANN field is split out into several separate fields according to the VCF Annotation Format standard.

Header Description
ALLELE Allele that the annotation applies to
ANNOTATION Effect or consequence of the variant, annotated using terms from the Sequence Ontology
IMPACT Estimation of the functional impact of the variant (one of: HIGH, MODERATE, LOW, MODIFIER)
GENE_NAME Common gene name
GENE_ID Identifier for the gene that the variant occurs in
FEATURE_TYPE Type of feature that is referred to in the FEATURE_ID field, using terms from the Sequence Ontology
FEATURE_ID Identifier for the sequence feature that the variant occurs in
TRANSCRIPT_BIOTYPE Type of transcript (coding, non-coding, etc.), corresponding to Ensembl biotypes
RANK Exon or Intron rank / total number of exons or introns
HGVS_C Variant using HGVS notation (DNA level)
HGVS_P If variant is coding, the variant using HGVS notation (Protein level).
CDS_POSITION Variant position in coding sequence (CDS)
CDS_LENGTH Coding sequence (CDS) length
CDNA_POSITION Variant position in cDNA sequence
CDNA_LENGTH cDNA length
AA_POSITION Variant position in amino acid sequence
AA_LENGTH Amino acid length
DISTANCE Distance to feature
ERRORS_WARNINGS_INFO Any errors, warnings or info related to variant annotation

All ANN fields are prefixed with ANN_ in the output .csv file.

Note that in the VCF Annotation Format standard, the fields CDS_POSITION and CDS_LENGTH are combined into a single slash-delimited field, as are the CDNA and AA position and length fields. They are parsed into separate fields in the .csv output of this tool.

As with the INFO field, the FORMAT field may include several sub-fields, which differ depending on the tool(s) used to produce the .vcf file. Some examples:

Header Description
GT Genotype
REF_GL Genotype likelihood (log-10 scaled) for the REF allele
ALT_GL Genotype likelihood (log-10 scaled) for the ALT allele
DP Read depth
AD Allele depth

All FORMAT fields are prefixed with FORMAT_ in the output .csv file.

Example

The following .vcf file:

##fileformat=VCFv4.2
##FILTER=<ID=PASS,Description="All filters passed">
##reference=ref.fa
##contig=<ID=MN908947.3,length=29903>
##phasing=none
##INFO=<ID=NS,Number=1,Type=Integer,Description="Number of samples with data">
##INFO=<ID=DP,Number=1,Type=Integer,Description="Total read depth at the locus">
##INFO=<ID=DPB,Number=1,Type=Float,Description="Total read depth per bp at the locus; bases in reads overlapping / bases in haplotype">
##INFO=<ID=AC,Number=A,Type=Integer,Description="Total number of alternate alleles in called genotypes">
##INFO=<ID=AN,Number=1,Type=Integer,Description="Total number of alleles in called genotypes">
##INFO=<ID=AF,Number=A,Type=Float,Description="Estimated allele frequency in the range (0,1]">
##INFO=<ID=RO,Number=1,Type=Integer,Description="Count of full observations of the reference haplotype.">
##INFO=<ID=AO,Number=A,Type=Integer,Description="Count of full observations of this alternate haplotype.">
##INFO=<ID=PRO,Number=1,Type=Float,Description="Reference allele observation count, with partial observations recorded fractionally">
##INFO=<ID=PAO,Number=A,Type=Float,Description="Alternate allele observations, with partial observations recorded fractionally">
##INFO=<ID=QR,Number=1,Type=Float,Description="Reference allele quality sum in phred">
##INFO=<ID=QA,Number=A,Type=Integer,Description="Alternate allele quality sum in phred">
##INFO=<ID=PQR,Number=1,Type=Float,Description="Reference allele quality sum in phred for partial observations">
##INFO=<ID=PQA,Number=A,Type=Float,Description="Alternate allele quality sum in phred for partial observations">
##INFO=<ID=SRF,Number=1,Type=Integer,Description="Number of reference observations on the forward strand">
##INFO=<ID=SRR,Number=1,Type=Integer,Description="Number of reference observations on the reverse strand">
##INFO=<ID=SAF,Number=A,Type=Integer,Description="Number of alternate observations on the forward strand">
##INFO=<ID=SAR,Number=A,Type=Integer,Description="Number of alternate observations on the reverse strand">
##INFO=<ID=SRP,Number=1,Type=Float,Description="Strand balance probability for the reference allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SRF and SRR given E(SRF/SRR) ~ 0.5, derived using Hoeffding's inequality">
##INFO=<ID=SAP,Number=A,Type=Float,Description="Strand balance probability for the alternate allele: Phred-scaled upper-bounds estimate of the probability of observing the deviation between SAF and SAR given E(SAF/SAR) ~ 0.5, derived using Hoeffding's inequality">
##INFO=<ID=AB,Number=A,Type=Float,Description="Allele balance at heterozygous sites: a number between 0 and 1 representing the ratio of reads showing the reference allele to all reads, considering only reads from individuals called as heterozygous">
##INFO=<ID=ABP,Number=A,Type=Float,Description="Allele balance probability at heterozygous sites: Phred-scaled upper-bounds estimate of the probability of observing the deviation between ABR and ABA given E(ABR/ABA) ~ 0.5, derived using Hoeffding's inequality">
##INFO=<ID=RUN,Number=A,Type=Integer,Description="Run length: the number of consecutive repeats of the alternate allele in the reference genome">
##INFO=<ID=RPP,Number=A,Type=Float,Description="Read Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
##INFO=<ID=RPPR,Number=1,Type=Float,Description="Read Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between RPL and RPR given E(RPL/RPR) ~ 0.5, derived using Hoeffding's inequality">
##INFO=<ID=RPL,Number=A,Type=Float,Description="Reads Placed Left: number of reads supporting the alternate balanced to the left (5') of the alternate allele">
##INFO=<ID=RPR,Number=A,Type=Float,Description="Reads Placed Right: number of reads supporting the alternate balanced to the right (3') of the alternate allele">
##INFO=<ID=EPP,Number=A,Type=Float,Description="End Placement Probability: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
##INFO=<ID=EPPR,Number=1,Type=Float,Description="End Placement Probability for reference observations: Phred-scaled upper-bounds estimate of the probability of observing the deviation between EL and ER given E(EL/ER) ~ 0.5, derived using Hoeffding's inequality">
##INFO=<ID=DPRA,Number=A,Type=Float,Description="Alternate allele depth ratio.  Ratio between depth in samples with each called alternate allele and those without.">
##INFO=<ID=ODDS,Number=1,Type=Float,Description="The log odds ratio of the best genotype combination to the second-best.">
##INFO=<ID=GTI,Number=1,Type=Integer,Description="Number of genotyping iterations required to reach convergence or bailout.">
##INFO=<ID=TYPE,Number=A,Type=String,Description="The type of allele, either snp, mnp, ins, del, or complex.">
##INFO=<ID=CIGAR,Number=A,Type=String,Description="The extended CIGAR representation of each alternaote allele, with the exception that '=' is replaced by 'M' to ease VCF parsing.  Note that INDEL alleles do not have the first matched base (which is provided by default, per the spec) referred to by the CIGAR.">
##INFO=<ID=NUMALT,Number=1,Type=Integer,Description="Number of unique non-reference alleles in called genotypes at this position.">
##INFO=<ID=MEANALT,Number=A,Type=Float,Description="Mean number of unique non-reference allele observations per sample with the corresponding alternate alleles.">
##INFO=<ID=LEN,Number=A,Type=Integer,Description="allele length">
##INFO=<ID=MQM,Number=A,Type=Float,Description="Mean mapping quality of observed alternate alleles">
##INFO=<ID=MQMR,Number=1,Type=Float,Description="Mean mapping quality of observed reference alleles">
##INFO=<ID=PAIRED,Number=A,Type=Float,Description="Proportion of observed alternate alleles which are supported by properly paired read fragments">
##INFO=<ID=PAIREDR,Number=1,Type=Float,Description="Proportion of observed reference alleles which are supported by properly paired read fragments">
##INFO=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
##INFO=<ID=END,Number=1,Type=Integer,Description="Last position (inclusive) in gVCF output record.">
##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
##FORMAT=<ID=GQ,Number=1,Type=Float,Description="Genotype Quality, the Phred-scaled marginal (or unconditional) probability of the called genotype">
##FORMAT=<ID=GL,Number=G,Type=Float,Description="Genotype Likelihood, log10-scaled likelihoods of the data given the called genotype for each possible genotype generated from the reference and alternate alleles given the sample ploidy">
##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read Depth">
##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Number of observation for each allele">
##FORMAT=<ID=RO,Number=1,Type=Integer,Description="Reference allele observation count">
##FORMAT=<ID=QR,Number=1,Type=Float,Description="Sum of quality of the reference observations">
##FORMAT=<ID=AO,Number=A,Type=Integer,Description="Alternate allele observation count">
##FORMAT=<ID=QA,Number=A,Type=Integer,Description="Sum of quality of the alternate observations">
##FORMAT=<ID=MIN_DP,Number=1,Type=Integer,Description="Minimum depth in gVCF output block.">
##INFO=<ID=VAF,Number=A,Type=Float,Description="Variant allele fraction, called from observed reference/alt reads">
##INFO=<ID=ANN,Number=.,Type=String,Description="Functional annotations: 'Allele | Annotation | Annotation_Impact | Gene_Name | Gene_ID | Feature_Type | Feature_ID | Transcript_BioType | Rank | HGVS.c | HGVS.p | cDNA.pos / cDNA.length | CDS.pos / CDS.length | AA.pos / AA.length | Distance | ERRORS / WARNINGS / INFO' ">
##INFO=<ID=LOF,Number=.,Type=String,Description="Predicted loss of function effects for this variant. Format: 'Gene_Name | Gene_ID | Number_of_transcripts_in_gene | Percent_of_transcripts_affected'">
##INFO=<ID=NMD,Number=.,Type=String,Description="Predicted nonsense mediated decay effects for this variant. Format: 'Gene_Name | Gene_ID | Number_of_transcripts_in_gene | Percent_of_transcripts_affected'">
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	sample-01
MN908947.3	241	.	C	T	20097.1	.	AB=0;ABP=0;AC=1;AF=1;AN=1;AO=610;CIGAR=1X;DP=610;DPB=610;DPRA=0;EPP=229.071;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=4627.53;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=22681;QR=0;RO=0;RPL=266;RPP=24.6681;RPPR=0;RPR=344;RUN=1;SAF=283;SAP=9.90206;SAR=327;SRF=0;SRP=0;SRR=0;TYPE=snp;VAF=1;ANN=T|upstream_gene_variant|MODIFIER|orf1ab|Gene_265_21554|transcript|QHD43415.1|protein_coding||c.-25C>T|||||25|,T|intergenic_region|MODIFIER|CHR_START-orf1ab|CHR_START-Gene_265_21554|intergenic_region|CHR_START-Gene_265_21554|||n.241C>T||||||	GT:DP:AD:RO:QR:AO:QA:GL	1:610:0,610:0:0:610:22681:-2040.3,0
MN908947.3	3037	.	C	T	17421.0	.	AB=0;ABP=0;AC=1;AF=1;AN=1;AO=515;CIGAR=1X;DP=515;DPB=515;DPRA=0;EPP=163.341;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=4011.34;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=19716;QR=0;RO=0;RPL=206;RPP=47.7426;RPPR=0;RPR=309;RUN=1;SAF=198;SAP=62.7195;SAR=317;SRF=0;SRP=0;SRR=0;TYPE=snp;VAF=1;ANN=T|synonymous_variant|LOW|orf1ab|Gene_265_21554|transcript|QHD43415.1|protein_coding|1/2|c.2772C>T|p.F924F|2772/21291|2772/21291|924/7096||	GT:DP:AD:RO:QR:AO:QA:GL	1:515:0,515:0:0:515:19716:-1773.38,0
MN908947.3	6248	.	A	C	8674.36	.	AB=0;ABP=0;AC=1;AF=1;AN=1;AO=265;CIGAR=1X;DP=265;DPB=265;DPRA=0;EPP=15.4737;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=1997.35;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=10146;QR=0;RO=0;RPL=176;RPP=65.0325;RPPR=0;RPR=89;RUN=1;SAF=36;SAP=308.237;SAR=229;SRF=0;SRP=0;SRR=0;TYPE=snp;VAF=1;ANN=C|missense_variant|MODERATE|orf1ab|Gene_265_21554|transcript|QHD43415.1|protein_coding|1/2|c.5983A>C|p.N1995H|5983/21291|5983/21291|1995/7096||	GT:DP:AD:RO:QR:AO:QA:GL	1:265:0,265:0:0:265:10146:-912.785,0
MN908947.3	14408	.	C	T	11344.9	.	AB=0;ABP=0;AC=1;AF=1;AN=1;AO=333;CIGAR=1X;DP=333;DPB=333;DPRA=0;EPP=30.5613;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=2612.26;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=12733;QR=0;RO=0;RPL=129;RPP=39.6906;RPPR=0;RPR=204;RUN=1;SAF=179;SAP=7.08589;SAR=154;SRF=0;SRP=0;SRR=0;TYPE=snp;VAF=1;ANN=T|missense_variant|MODERATE|orf1ab|Gene_265_21554|transcript|QHD43415.1|protein_coding|2/2|c.14144C>T|p.P4715L|14144/21291|14144/21291|4715/7096||	GT:DP:AD:RO:QR:AO:QA:GL	1:333:0,333:0:0:333:12733:-1145.43,0
MN908947.3	20268	.	A	G	7808.6	.	AB=0;ABP=0;AC=1;AF=1;AN=1;AO=230;CIGAR=1X;DP=230;DPB=230;DPRA=0;EPP=3.95442;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=1798;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=8736;QR=0;RO=0;RPL=131;RPP=12.6781;RPPR=0;RPR=99;RUN=1;SAF=123;SAP=5.42724;SAR=107;SRF=0;SRP=0;SRR=0;TYPE=snp;VAF=1;ANN=G|synonymous_variant|LOW|orf1ab|Gene_265_21554|transcript|QHD43415.1|protein_coding|2/2|c.20004A>G|p.L6668L|20004/21291|20004/21291|6668/7096||,G|upstream_gene_variant|MODIFIER|S|Gene_21562_25383|transcript|QHD43416.1|protein_coding||c.-1295A>G|||||1295|	GT:DP:AD:RO:QR:AO:QA:GL	1:230:0,230:0:0:230:8736:-785.999,0
MN908947.3	23403	.	A	G	17799.4	.	AB=0;ABP=0;AC=1;AF=1;AN=1;AO=530;CIGAR=1X;DP=530;DPB=530;DPRA=0;EPP=124.219;EPPR=0;GTI=0;LEN=1;MEANALT=1;MQM=60;MQMR=0;NS=1;NUMALT=1;ODDS=4098.47;PAIRED=1;PAIREDR=0;PAO=0;PQA=0;PQR=0;PRO=0;QA=20075;QR=0;RO=0;RPL=253;RPP=5.37024;RPPR=0;RPR=277;RUN=1;SAF=192;SAP=90.3445;SAR=338;SRF=0;SRP=0;SRR=0;TYPE=snp;VAF=1;ANN=G|missense_variant|MODERATE|S|Gene_21562_25383|transcript|QHD43416.1|protein_coding|1/1|c.1841A>G|p.D614G|1841/3822|1841/3822|614/1273||,G|upstream_gene_variant|MODIFIER|ORF3a|Gene_25392_26219|transcript|QHD43417.1|protein_coding||c.-1990A>G|||||1990|,G|upstream_gene_variant|MODIFIER|E|Gene_26244_26471|transcript|QHD43418.1|protein_coding||c.-2842A>G|||||2842|,G|upstream_gene_variant|MODIFIER|M|Gene_26522_27190|transcript|QHD43419.1|protein_coding||c.-3120A>G|||||3120|,G|upstream_gene_variant|MODIFIER|ORF6|Gene_27201_27386|transcript|QHD43420.1|protein_coding||c.-3799A>G|||||3799|,G|upstream_gene_variant|MODIFIER|ORF7a|Gene_27393_27758|transcript|QHD43421.1|protein_coding||c.-3991A>G|||||3991|,G|upstream_gene_variant|MODIFIER|ORF8|Gene_27893_28258|transcript|QHD43422.1|protein_coding||c.-4491A>G|||||4491|,G|upstream_gene_variant|MODIFIER|N|Gene_28273_29532|transcript|QHD43423.2|protein_coding||c.-4871A>G|||||4871|,G|downstream_gene_variant|MODIFIER|orf1ab|Gene_265_21554|transcript|QHD43415.1|protein_coding||c.*1848A>G|||||1848|	GT:DP:AD:RO:QR:AO:QA:GL	1:530:0,530:0:0:530:20075:-1805.71,0

..produces the following 'melted' .csv:

SAMPLE,CHROM,POS,ID,REF,ALT,QUAL,FILTER,INFO_NS,INFO_DP,INFO_DPB,INFO_AC,INFO_AN,INFO_AF,INFO_RO,INFO_AO,INFO_PRO,INFO_PAO,INFO_QR,INFO_QA,INFO_PQR,INFO_PQA,INFO_SRF,INFO_SRR,INFO_SAF,INFO_SAR,INFO_SRP,INFO_SAP,INFO_AB,INFO_ABP,INFO_RUN,INFO_RPP,INFO_RPPR,INFO_RPL,INFO_RPR,INFO_EPP,INFO_EPPR,INFO_DPRA,INFO_ODDS,INFO_GTI,INFO_TYPE,INFO_CIGAR,INFO_NUMALT,INFO_MEANALT,INFO_LEN,INFO_MQM,INFO_MQMR,INFO_PAIRED,INFO_PAIREDR,INFO_VAF,ANN_ALLELE,ANN_ANNOTATION,ANN_IMPACT,ANN_GENE_NAME,ANN_GENE_ID,ANN_FEATURE_TYPE,ANN_FEATURE_ID,ANN_TRANSCRIPT_BIOTYPE,ANN_RANK,ANN_HGVS_C,ANN_HGVS_P,ANN_CDS_POSITION,ANN_CDS_LENGTH,ANN_AA_POSITION,ANN_AA_LENGTH,ANN_CDNA_POSITION,ANN_CDNA_LENGTH,ANN_DISTANCE,ANN_ERRORS_WARNINGS_INFO,FORMAT_GT,FORMAT_REF_GL,FORMAT_ALT_GL,FORMAT_DP,FORMAT_AD,FORMAT_RO,FORMAT_QR,FORMAT_AO,FORMAT_QA
sample-01,MN908947.3,241,.,C,T,20097.1,.,1,610,610.0,1,1,1.0,0,610,0.0,0.0,0.0,22681,0.0,0.0,0,0,283,327,0.0,9.90206,0.0,0.0,1,24.6681,0.0,266.0,344.0,229.071,0.0,0.0,4627.53,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,T,upstream_gene_variant,MODIFIER,orf1ab,Gene_265_21554,transcript,QHD43415.1,protein_coding,,c.-25C>T,,,,,,,,25,,1,-2040.3,0.0,610,0,0,0.0,610,22681
sample-01,MN908947.3,241,.,C,T,20097.1,.,1,610,610.0,1,1,1.0,0,610,0.0,0.0,0.0,22681,0.0,0.0,0,0,283,327,0.0,9.90206,0.0,0.0,1,24.6681,0.0,266.0,344.0,229.071,0.0,0.0,4627.53,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,T,intergenic_region,MODIFIER,CHR_START-orf1ab,CHR_START-Gene_265_21554,intergenic_region,CHR_START-Gene_265_21554,,,n.241C>T,,,,,,,,,,1,-2040.3,0.0,610,0,0,0.0,610,22681
sample-01,MN908947.3,3037,.,C,T,17421.0,.,1,515,515.0,1,1,1.0,0,515,0.0,0.0,0.0,19716,0.0,0.0,0,0,198,317,0.0,62.7195,0.0,0.0,1,47.7426,0.0,206.0,309.0,163.341,0.0,0.0,4011.34,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,T,synonymous_variant,LOW,orf1ab,Gene_265_21554,transcript,QHD43415.1,protein_coding,1/2,c.2772C>T,p.F924F,2772,21291,2772,21291,924,7096,,,1,-1773.38,0.0,515,0,0,0.0,515,19716
sample-01,MN908947.3,6248,.,A,C,8674.36,.,1,265,265.0,1,1,1.0,0,265,0.0,0.0,0.0,10146,0.0,0.0,0,0,36,229,0.0,308.237,0.0,0.0,1,65.0325,0.0,176.0,89.0,15.4737,0.0,0.0,1997.35,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,C,missense_variant,MODERATE,orf1ab,Gene_265_21554,transcript,QHD43415.1,protein_coding,1/2,c.5983A>C,p.N1995H,5983,21291,5983,21291,1995,7096,,,1,-912.785,0.0,265,0,0,0.0,265,10146
sample-01,MN908947.3,14408,.,C,T,11344.9,.,1,333,333.0,1,1,1.0,0,333,0.0,0.0,0.0,12733,0.0,0.0,0,0,179,154,0.0,7.08589,0.0,0.0,1,39.6906,0.0,129.0,204.0,30.5613,0.0,0.0,2612.26,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,T,missense_variant,MODERATE,orf1ab,Gene_265_21554,transcript,QHD43415.1,protein_coding,2/2,c.14144C>T,p.P4715L,14144,21291,14144,21291,4715,7096,,,1,-1145.43,0.0,333,0,0,0.0,333,12733
sample-01,MN908947.3,20268,.,A,G,7808.6,.,1,230,230.0,1,1,1.0,0,230,0.0,0.0,0.0,8736,0.0,0.0,0,0,123,107,0.0,5.42724,0.0,0.0,1,12.6781,0.0,131.0,99.0,3.95442,0.0,0.0,1798.0,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,synonymous_variant,LOW,orf1ab,Gene_265_21554,transcript,QHD43415.1,protein_coding,2/2,c.20004A>G,p.L6668L,20004,21291,20004,21291,6668,7096,,,1,-785.999,0.0,230,0,0,0.0,230,8736
sample-01,MN908947.3,20268,.,A,G,7808.6,.,1,230,230.0,1,1,1.0,0,230,0.0,0.0,0.0,8736,0.0,0.0,0,0,123,107,0.0,5.42724,0.0,0.0,1,12.6781,0.0,131.0,99.0,3.95442,0.0,0.0,1798.0,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,upstream_gene_variant,MODIFIER,S,Gene_21562_25383,transcript,QHD43416.1,protein_coding,,c.-1295A>G,,,,,,,,1295,,1,-785.999,0.0,230,0,0,0.0,230,8736
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,missense_variant,MODERATE,S,Gene_21562_25383,transcript,QHD43416.1,protein_coding,1/1,c.1841A>G,p.D614G,1841,3822,1841,3822,614,1273,,,1,-1805.71,0.0,530,0,0,0.0,530,20075
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,upstream_gene_variant,MODIFIER,ORF3a,Gene_25392_26219,transcript,QHD43417.1,protein_coding,,c.-1990A>G,,,,,,,,1990,,1,-1805.71,0.0,530,0,0,0.0,530,20075
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,upstream_gene_variant,MODIFIER,E,Gene_26244_26471,transcript,QHD43418.1,protein_coding,,c.-2842A>G,,,,,,,,2842,,1,-1805.71,0.0,530,0,0,0.0,530,20075
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,upstream_gene_variant,MODIFIER,M,Gene_26522_27190,transcript,QHD43419.1,protein_coding,,c.-3120A>G,,,,,,,,3120,,1,-1805.71,0.0,530,0,0,0.0,530,20075
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,upstream_gene_variant,MODIFIER,ORF6,Gene_27201_27386,transcript,QHD43420.1,protein_coding,,c.-3799A>G,,,,,,,,3799,,1,-1805.71,0.0,530,0,0,0.0,530,20075
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,upstream_gene_variant,MODIFIER,ORF7a,Gene_27393_27758,transcript,QHD43421.1,protein_coding,,c.-3991A>G,,,,,,,,3991,,1,-1805.71,0.0,530,0,0,0.0,530,20075
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,upstream_gene_variant,MODIFIER,ORF8,Gene_27893_28258,transcript,QHD43422.1,protein_coding,,c.-4491A>G,,,,,,,,4491,,1,-1805.71,0.0,530,0,0,0.0,530,20075
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,upstream_gene_variant,MODIFIER,N,Gene_28273_29532,transcript,QHD43423.2,protein_coding,,c.-4871A>G,,,,,,,,4871,,1,-1805.71,0.0,530,0,0,0.0,530,20075
sample-01,MN908947.3,23403,.,A,G,17799.4,.,1,530,530.0,1,1,1.0,0,530,0.0,0.0,0.0,20075,0.0,0.0,0,0,192,338,0.0,90.3445,0.0,0.0,1,5.37024,0.0,253.0,277.0,124.219,0.0,0.0,4098.47,0,snp,1X,1,1.0,1,60.0,0.0,1.0,0.0,1.0,G,downstream_gene_variant,MODIFIER,orf1ab,Gene_265_21554,transcript,QHD43415.1,protein_coding,,c.*1848A>G,,,,,,,,1848,,1,-1805.71,0.0,530,0,0,0.0,530,20075

vcf-melt's People

Contributors

dfornika avatar

Watchers

avatar

vcf-melt's Issues

Consider not coverting headers in output

The vcf_melt.py script currently translates the field names from the vcf input into more human-readable terms. This makes the output more directly easy to understand, but it has some downsides:

  • An opinionated mapping of vcf fields to headers is hard-coded into the tool. See:

    vcf-melt/vcf_melt/vcf_melt.py

    Lines 57 to 68 in 7e4fe1b

    formats_lookup = {
    'GT': 'genotype',
    'GQ': 'genotype_quality',
    'GL': 'genotype_likelihood',
    'DP': 'read_depth',
    'AD': 'allele_depth',
    'RO': 'ref_allele_observation_count',
    'QR': 'sum_quality_of_ref_observations',
    'AO': 'alt_allele_observation_count',
    'QA': 'sum_quality_of_alt_observations',
    'MIN_DP': 'minimum_depth_gvcf',
    }

    vcf-melt/vcf_melt/vcf_melt.py

    Lines 71 to 119 in 7e4fe1b

    infos_lookup = {
    'NS': 'num_samples',
    'DP': 'total_depth',
    'DPB': 'total_depth_per_bp',
    'AC': 'alt_alleles',
    'AN': 'num_alleles',
    'AF': 'estimated_allele_freq',
    'RO': 'num_ref_haplotype',
    'AO': 'num_alt_haplotype',
    'PRO': 'num_ref_haplotypes_with_partial',
    'PAO': 'num_alt_haplotypes_with_partial',
    'QR': 'sum_quality_of_ref_observations',
    'QA': 'sum_quality_of_alt_observations',
    'PQR': 'sum_quality_of_partial_ref_observations',
    'PQA': 'sum_quality_of_partial_alt_observations',
    'SRF': 'num_ref_observations_fwd_strand',
    'SRR': 'num_ref_observations_rev_strand',
    'SAF': 'num_alt_observations_fwd_strand',
    'SAR': 'num_alt_observations_rev_strand',
    'SRP': 'strand_balance_probability_ref_allele',
    'SAP': 'strand_balance_probability_alt_allele',
    'AB': 'allele_balance_het_sites',
    'ABP': 'allele_balance_probability_het_sites',
    'RUN': 'run_length',
    'RPP': 'read_placement_probability',
    'RPPR': 'read_placement_probability_ref',
    'RPL': 'reads_placed_left',
    'RPR': 'reads_placed_right',
    'EPP': 'end_placement_probability',
    'EPPR': 'end_placement_probability_ref',
    'DPRA': 'alt_allele_depth_ratio',
    'ODDS': 'log_odds_ratio',
    'GTI': 'genotyping_iterations',
    'TYPE': 'variant_type',
    'CIGAR': 'cigar_alt',
    'NUMALT': 'num_alt_alleles',
    'MEANALT': 'mean_num_alt_alleles',
    'LEN': 'allele_length',
    'MQM': 'mean_mapping_quality_alt',
    'MQMR': 'mean_mapping_quality_ref',
    'PAIRED': 'proportion_properly_paired_alt',
    'PAIREDR': 'proportion_properly_paired_ref',
    'MIN_DP': 'min_depth_gvcf',
    'END': 'end_gvcf',
    'VAF': 'variant_allele_fraction',
    'ANN': 'functional_annotation',
    'LOF': 'loss_of_function',
    'NMD': 'nonsense_mediated_decay',
    }
  • The set of vcf fields that are supported is hard-coded into the tool. If other vcf outputs include additional INFO or FORMAT fields, they will not be supported unless the script is modified.

An alternative approach would be to use the vcf field IDs as headers directly, then use another tool to map the headers to more human-readable values. One downside to that approach is that there are sub-fields within the ANN INFO field that have no clear headers stored within the .vcf. There is, howerver, a standard format for the ANN field that is supported by common annotation tools like snpEff:

https://pcingola.github.io/SnpEff/adds/VCFannotationformat_v1.0.pdf

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.