Polyphonia: detecting inter-sample contamination in viral genomic sequencing data

• DOI: 10.1093/bioinformatics/btae698
• Publication Date: 2024-12-14T11:51:57Z
• Authors: Lydia A Krasilnikova; Christopher H Tom...; Alton C Gayton; Stephen F Schaffner; Sabrina T Dobbins; Adrianne Gladden-...; Katherine J Siddle; Daniel J Park; Pardis C Sabeti
• Keywords: 0301 basic medicine; Applications Note; 03 medical and health sciences

Abstract

Summary In viral genomic research and surveillance, inter-sample contamination can affect variant detection, analysis of within-host evolution, outbreak reconstruction, and detection of superinfections and recombination events. While sample barcoding methods exist to track inter-sample contamination, they are not always used and can only detect contamination in the experimental pipeline from the point they are added. The underlying genomic information in a sample, however, carries information about inter-sample contamination occurring at any stage. Here, we present Polyphonia, a tool for detecting inter-sample contamination directly from deep sequencing data without the need for additional controls, using intrahost variant frequencies. We apply Polyphonia to 1102 SARS-CoV-2 samples sequenced at the Broad Institute and already tracked using molecular barcoding for comparison.

Availability and implementation Polyphonia is available as a standalone Docker image and is also included as part of viral-ngs, available in Dockstore. Full documentation, source code, and instructions for use are available at https://github.com/broadinstitute/polyphonia.