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Updated: Jun 5, 2025

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples
Published on: July 2, 2016
Polyphonia: detecting inter-sample contamination in viral genomic sequencing data
Lydia A Krasilnikova1,2,3, Christopher H Tomkins-Tinch2, Alton C Gayton4
1Howard Hughes Medical Institute, Chevy Chase, MD 20815, United States.
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.

