2022
DOI: 10.21105/joss.03722
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Bam-readcount - rapid generation of basepair-resolution sequence metrics

Abstract: Bam-readcount is a utility for generating low-level information about sequencing data at specific nucleotide positions. Originally designed to help filter genomic mutation calls, the metrics it outputs are useful as input for variant detection tools and for resolving ambiguity between variant callers (Koboldt et al., 2013a;Kothen-Hill et al., 2018). In addition, it has found broad applicability in diverse fields including tumor evolution, single-cell genomics, climate change ecology, and tracking community spr… Show more

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Cited by 54 publications
(38 citation statements)
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“…We applied the SNP-sites tool33 to identify single nucleotide variations (SNVs) based on the MAFFT-alignment of the consensus sequence of case 2 and the reference genome mentioned above. SNVs were checked for sequencing depth and agreement on the sequencing data for the alternative allele using the tool bam-readcount 34.…”
mentioning
confidence: 99%
“…We applied the SNP-sites tool33 to identify single nucleotide variations (SNVs) based on the MAFFT-alignment of the consensus sequence of case 2 and the reference genome mentioned above. SNVs were checked for sequencing depth and agreement on the sequencing data for the alternative allele using the tool bam-readcount 34.…”
mentioning
confidence: 99%
“…Allele-specific copy number alterations were called using FACETS [17]. Somatic mutations were called using a consensus method to reduce false positives, and bam-readcount [18] was used to compute variant allele frequencies (VAFs). Variants called in at least two of three methods, Mutect2 [16], Lancet [19], and Strelka [20], with at least 10 reads supporting the alternate allele, were retained for further analysis.…”
Section: Whole-exome Sequencingmentioning
confidence: 99%
“…To filter out the FFPE artefacts, we employed Support Vector Machine-based (SVM) methodology with the e1071 R library. 51 For each sample separately, each variant in the prefiltered VCF file (the same filters as for the fresh non-FFPE samples) was annotated with additional quality information specific for the alternative allele from the BAM file using bam-readcount utility 52 . This additional BAM-derived information in the form of a table was merged with the quality annotations from the VCF file (VCF was parsed into a table with vcf2tsv from vcflib library 53 ) which included CONTQ (Phred-scaled qualities that alt allele are not due to contamination), SEQQ (Phred-scaled quality that alt alleles are not sequencing errors), STRANDQ (Phred-scaled quality of strand bias artifact), TLOD (Log 10 likelihood ratio score of variant existing versus not existing).…”
Section: Methodsmentioning
confidence: 99%