ArticleGigaScience2025
Finding easy regions for short-read variant calling from pangenome data.
Article in GigaScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Pangenome Dynamics and Functional Diversification in the Marine Genus Pseudoalteromonas: Association to Colony Pigmentation.Marine biotechnology (New York, N.Y.) · 2026Article
- Pangenome-based human genome analysis improves trait association and genomic prediction.bioRxiv : the preprint server for biology · 2026Article
- Population-scale Y chromosome assemblies reveal recurrent remodeling within constrained architectures.bioRxiv : the preprint server for biology · 2026Article
- Functional impact of genetic background on variable expressivity in neurodevelopmental disorders.Nature communications · 2026Article
- Finding low-complexity DNA sequences with longdust.Bioinformatics (Oxford, England) · 2026Article
- MosaicSim: A Novel Mosaic Variant Simulator Reveals Diminishing Returns of Ultra-High Coverage for Mosaic Variant Detection.bioRxiv : the preprint server for biology · 2025Article
- Comprehensive benchmarking of somatic single-nucleotide variant and indel detection at ultra-low allele fractions using short- and long-read data.bioRxiv : the preprint server for biology · 2025Article
- Multi-platform framework for mapping somatic retrotransposition in human tissues.bioRxiv : the preprint server for biology · 2025Article
- Finding easy regions for short-read variant calling from pangenome data.GigaScience · 2025Article
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Abstract
backgroundWhile benchmarks on short-read variant calling suggest a low error rate below 0.5%, they are only applicable to predefined confident regions. For a human sample without such regions, the error rate could be 10 times higher. Although multiple sets of easy regions have been identified to alleviate the issue, they fail to consider nonreference samples or are biased toward existing short-read data or aligners.
resultsHere, using hundreds of high-quality human assemblies, we derived a set of sample-agnostic easy regions where short-read variant calling reaches high accuracy. These regions cover 88.2% of GRCh38, 92.2% of coding regions, and 96.3% of ClinVar pathogenic variants. They achieve a good balance between coverage and easiness and can be generated for other human assemblies or species with multiple well-assembled genomes.
conclusionsThis resource provides a convenient and powerful way to filter spurious variant calls for clinical or research human samples.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.