Sample-Index Misassignment Impacts Tumour Exome Sequencing.

Area of Science:

• Genomics
• Bioinformatics
• Cancer Research

Background:

• Sample pooling with dedicated indexes is standard for cost-effective, high-throughput sequencing.
• Index misassignment, or cross-contamination, is a known issue in Illumina sequencing, particularly with exclusion amplification.

Purpose of the Study:

• To investigate the impact of index misassignment on variant calling in real-world tumor sequencing data.
• To highlight the potential for artefactual variants to be mistaken for genuine somatic mutations.
• To discuss mitigation strategies and provide tools for identifying misassignment-induced variants.

Main Methods:

• Analysis of real-life sequencing data from multiple tumor projects.
• Evaluation of variant calls for potential artefactual origins due to index misassignment.
• Development of software to aid in the identification of such variants.

Main Results:

• Demonstrated that index misassignment can generate artefactual variant calls that resemble true somatic variants.
• Observed that these artefactual calls are particularly problematic for analyses at low allelic frequencies, such as in tumor clonal analysis.
• Confirmed the potential for significant impact on cancer genomics studies.

Conclusions:

• Index misassignment poses a significant challenge in high-throughput sequencing, potentially leading to erroneous conclusions in cancer research.
• Improved library indexing methods and dedicated software are crucial for accurate variant detection and reliable clonal analysis in tumors.
• The developed software can assist researchers in identifying and mitigating the effects of index misassignment.