MuCor: mutation aggregation and correlation.

Area of Science:

• Genomics
• Bioinformatics
• Computational Biology

Background:

• Variant calling and effect prediction tools are numerous, but lack integration for large-scale cohort analysis.
• Current methods for aggregating and summarizing cohort variants often rely on custom, project-specific scripts.
• This necessitates significant re-development effort for each new large-scale genetic study.

Purpose of the Study:

• To introduce MuCor, a novel bioinformatics tool designed to streamline the aggregation, sorting, and summarization of genetic variants across large sample groups.
• To provide a versatile solution for analyzing variants from diverse input formats and performing database lookups and frequency calculations.
• To enable direct comparison of variant calls from the same sample across multiple platforms or pipelines, and to introduce DepthGauge for coverage assessment.

Main Methods:

• MuCor accepts variants from various input formats, including multiple files per sample.
• It integrates database lookups and calculates variant frequencies within cohorts.
• MuCor generates multiple report types and includes a companion tool, DepthGauge, for region-specific coverage analysis.

Main Results:

• MuCor effectively aggregates and summarizes genetic variants from large sample cohorts.
• The tool facilitates direct comparison of variant calls across different platforms or pipelines for the same sample.
• DepthGauge enhances confidence in variant calls by measuring coverage at regions of interest.

Conclusions:

• MuCor provides a unified and efficient solution for cohort-level variant analysis, reducing the need for ad hoc scripting.
• The tool supports large-scale genetic studies and facilitates cross-platform variant call comparisons.
• MuCor and DepthGauge improve the robustness and interpretability of genetic variant data.