Francesc-Muyas
commented
1 year ago Dear user, Thanks for using our tool and for bringing up this interesting question.
In our manuscript, we have annotated all our variants using annovar. With a couple of command lines, we can adapt our variant calling output for this annotation tool. Using our example data, we should run these lines:
1. Preparing SComatic output for annovar
ANNOVAR=/path/to/annovar
hummandb=/path/to/annovar_humandb_hg38
grep -v '#' Example.calling.step2.pass.tsv | tr '\t' '-' | awk -F'-' -v OFS='\t' '{print $1,$2,$3,$4,$5,$0}' > sample.variants.avinput2. Annotate variants using the annovar-ready variant file
perl $ANNOVAR/table_annovar.pl sample.variants.avinput \
$hummandb -buildver hg38 \
-out sample.variants.annovar \
-remove -protocol refGene,cytoBand,exac03,avsnp147,dbnsfp30a,gnomad_genome -operation g,r,f,f,f,f \
-nastring . -csvout -polish --otherinfoThis step will generate a comma-separated file (.csv) called _sample.variants.annovar.hg38multianno.csv , which can be easily opened and processed in your more desired software (R, excel...). The output should look like this:
Chr,Start,End,Ref,Alt,Func.refGene,Gene.refGene,GeneDetail.refGene,ExonicFunc.refGene,AAChange.refGene,cytoBand,ExAC_ALL,ExAC_AFR,ExAC_AMR,ExAC_EAS,ExAC_FIN,ExAC_NFE,ExAC_OTH,ExAC_SAS,avsnp147,SIFT_score,SIFT_pred,Polyphen2_HDIV_score,Polyphen2_HDIV_pred,Polyphen2_HVAR_score,Polyphen2_HVAR_pred,LRT_score,LRT_pred,MutationTaster_score,MutationTaster_pred,MutationAssessor_score,MutationAssessor_pred,FATHMM_score,FATHMM_pred,PROVEAN_score,PROVEAN_pred,VEST3_score,CADD_raw,CADD_phred,DANN_score,fathmm-MKL_coding_score,fathmm-MKL_coding_pred,MetaSVM_score,MetaSVM_pred,MetaLR_score,MetaLR_pred,integrated_fitCons_score,integrated_confidence_value,GERP++_RS,phyloP7way_vertebrate,phyloP20way_mammalian,phastCons7way_vertebrate,phastCons20way_mammalian,SiPhy_29way_logOdds,gnomAD_genome_ALL,gnomAD_genome_AFR,gnomAD_genome_AMR,gnomAD_genome_ASJ,gnomAD_genome_EAS,gnomAD_genome_FIN,gnomAD_genome_NFE,gnomAD_genome_OTH,Otherinfo
chr10,29559501,29559501,A,T,"intronic","SVIL",.,.,.,"10p11.23",.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,"chr10-29559501-29559501-A-T-PASS-Epithelial_cells-ATTCA-TTGAT-1-12-5-4-2-0.3333-0.4-0.0-0.0001-2-2-0;38;1-0;16;1-.-PASS-DP|NC|CC|BC|BQ|BCf|BCr-NA-12|5|3:0:2:0:0:0|8:0:4:0:0:0|306:0:164:0:0:0|0:0:0:0:0:0|8:0:4:0:0:0-30|13|13:0:0:0:0:0|30:0:0:0:0:0|1189:0:0:0:0:0|0:0:0:0:0:0|30:0:0:0:0:0"
chr10,73413109,73413109,G,A,"intronic","ANXA7",.,.,.,"10q22.2",.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,"chr10-73413109-73413109-G-A-PASS-Epithelial_cells-TGGAG-CATGG-1-12-8-4-3-0.3333-0.375-0.0-0.0-2-2-0;15;1-0;11;1-.-PASS-DP|NC|CC|BC|BQ|BCf|BCr-NA-12|8|3:0:0:5:0:0|4:0:0:8:0:0|160:0:0:302:0:0|0:0:0:0:0:0|4:0:0:8:0:0-7|6|0:0:0:6:0:0|0:0:0:7:0:0|0:0:0:270:0:0|0:0:0:0:0:0|0:0:0:7:0:0"
chr10,89413978,89413978,G,A,"upstream","IFIT5","dist=590",.,.,"10q23.31",.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,"chr10-89413978-89413978-G-A-PASS-Epithelial_cells-GTATG-GTGTT-1-18-11-7-4-0.3889-0.3636-0.0-0.0-2-2-0;20;1-0;12;1-.-PASS-DP|NC|CC|BC|BQ|BCf|BCr-NA-18|11|4:0:0:7:0:0|7:0:0:11:0:0|270:0:0:417:0:0|0:0:0:0:0:0|7:0:0:11:0:0-9|5|0:0:0:5:0:0|0:0:0:9:0:0|0:0:0:339:0:0|0:0:0:0:0:0|0:0:0:9:0:0"
chr10,97332670,97332670,G,A,"UTR3","FRAT2","NM_012083:c.*1201C>T",.,.,"10q24.1",.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,"chr10-97332670-97332670-G-A-PASS-Epithelial_cells-TTGGG-GTGGC-1-12-11-6-6-0.5-0.5455-0.0-0.0-2-2-0;12;1-0;11;1-.-PASS-DP|NC|CC|BC|BQ|BCf|BCr-6|6|0:0:0:6:0:0|0:0:0:6:0:0|0:0:0:237:0:0|0:0:0:0:0:0|0:0:0:6:0:0-12|11|6:0:0:5:0:0|6:0:0:6:0:0|229:0:0:225:0:0|0:0:0:0:0:0|6:0:0:6:0:0-NA"
chr10,126926205,126926205,G,A,"intronic","DOCK1",.,.,.,"10q26.2",.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,"chr10-126926205-126926205-G-A-PASS-Epithelial_cells-GATCC-GTGAC-1-35-17-15-6-0.4286-0.3529-0.0-0.0-2-2-0;35;1-0;18;1-.-PASS-DP|NC|CC|BC|BQ|BCf|BCr-NA-35|17|6:0:0:12:0:0|15:0:0:20:0:0|603:0:0:786:0:0|15:0:0:20:0:0|0:0:0:0:0:0-15|7|0:0:0:7:0:0|0:0:0:15:0:0|0:0:0:590:0:0|0:0:0:15:0:0|0:0:0:0:0:0"As you will notice, the first few columns of the file have the annotation information provided by annovar (Gene, region, impact, Gnomad allele frequencies...). Importantly, the final column of the csv file (Otherinfo) shows all the info found in the original Example.calling.step2.pass.tsv, but separated by the symbol "-" . The column names of each one of these Otherinfo items are the same as the ones found in the Example.calling.step2.pass.tsv :
> grep '^#CHROM' Example.calling.step2.pass.tsv
#CHROM Start End REF ALT FILTER Cell_types Up_context Down_context N_ALT Dp Nc Bc Cc VAF CCF BCp CCp Cell_types_min_BC Cell_types_min_CC Rest_BC Rest_CC Fisher_p Cell_type_Filter INFO Myeloids Epithelial_cells Stromal_cells
Of course, depending on the columns you want to keep for the annotation process, you might slightly change the command line in the step 1 described above, as well as the parameters provided in the annovar computation. The parameters provided here are the ones used in our manuscript.
Thanks again for your feedback, Fran
Hey, great tool! I just had a follow-up question. I ran your pipeline and everything went down smoothly. I was wondering if you had come up with a solution to annotate variants (i.e. obtain gene, cDNA, protein change annotation on the variants reported), since the output files do not look like canonical VCFs. Tools like funcotator or others require state of the art VCF files to run. It is also possible that I missed this step in your pipeline. Thank you in advance, FJ