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Measuring, visualizing, and diagnosing reference bias with biastools
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DOI：10.1186/s13059-024-03240-8.png)
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摘要
En 中文
Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it. Biastools analyzes and categorizes instances of reference bias. It works in various scenarios: when the donor's variants are known and reads are simulated; when donor variants are known and reads are real; and when variants are unknown and reads are real. Using biastools, we observe that more inclusive graph genomes result in fewer biased sites. We find that end-to-end alignment reduces bias at indels relative to local aligners. Finally, we use biastools to characterize how T2T references improve large-scale bias.
Keyword:
Reference bias
Sequence alignment
Pangenomics
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