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xAtlas: scalable small variant calling across heterogeneous next-generation sequencing experiments
Jesse Farek1, Daniel Hughes1,2, William Salerno1,3
1Human Genome Sequencing Center, One Baylor Plaza, Baylor College of Medicine, Houston, TX 77030, USA.
Gigascience
|January 16, 2023
Summary
xAtlas is a new DNA variant caller for next-generation sequencing (NGS) data. It accurately identifies single-nucleotide variants (SNVs) and small insertions/deletions (indels) rapidly, even with large datasets.
Area of Science:
- Genomics and Bioinformatics
- Computational Biology
Background:
- Next-generation sequencing (NGS) generates vast and diverse data, challenging DNA variation identification.
- Existing validation methods often rely on small, homogeneous sample sets, limiting their applicability.
Purpose of the Study:
- To develop an optimized variant caller for NGS data.
- To address the limitations of current methods in handling large and heterogeneous datasets.
Main Methods:
- Developed xAtlas, a single-sample variant caller for SNVs and indels.
- xAtlas supports CRAM and gVCF formats and features retraining capabilities.
- Evaluated performance on a reference HG002 sample and 3,202 samples from the 1000 Genomes Project.
Main Results:
- xAtlas achieved 99.11% recall and 98.43% precision for SNVs on a reference sample in under 2 CPU hours.
- Processing 3,202 samples from the 1000 Genomes Project averaged 1.7 hours per sample.
- Called SNVs clearly separated individual populations in principal component analysis.
Conclusions:
- xAtlas is a fast, lightweight, and accurate method for SNV and small indel calling.
- The tool is suitable for large-scale genomic analyses.
- Source code is publicly available.
