Details

Autor(en) / Beteiligte

• Yan, Melissa Y
• Ferguson, Betsy
• Bimber, Benjamin N
• Wren, Jonathan

Titel

VariantQC: a visual quality control report for variant evaluation

Ist Teil von

• Bioinformatics (Oxford, England), 2019-12, Vol.35 (24), p.5370-5371

Ort / Verlag

England: Oxford University Press

Erscheinungsjahr

2019

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Large scale genomic studies produce millions of sequence variants, generating datasets far too massive for manual inspection. To ensure variant and genotype data are consistent and accurate, it is necessary to evaluate variants prior to downstream analysis using quality control (QC) reports. Variant call format (VCF) files are the standard format for representing variant data; however, generating summary statistics from these files is not always straightforward. While tools to summarize variant data exist, they generally produce simple text file tables, which still require additional processing and interpretation. VariantQC fills this gap as a user friendly, interactive visual QC report that generates and concisely summarizes statistics from VCF files. The report aggregates and summarizes variants by dataset, chromosome, sample and filter type. The VariantQC report is useful for high-level dataset summary, quality control and helps flag outliers. Furthermore, VariantQC operates on VCF files, so it can be easily integrated into many existing variant pipelines. DISCVRSeq's VariantQC tool is freely available as a Java program, with the compiled JAR and source code available from https://github.com/BimberLab/DISCVRSeq/. Documentation and example reports are available at https://bimberlab.github.io/DISCVRSeq/.