Measuring, visualizing and diagnosing reference bias with biastools.
Measuring, visualizing and diagnosing reference bias with biastools.
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使用偏差工具测量、可视化和诊断参考偏差。
DOI：
10.1101/2023.09.13.557552
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发表时间：
2024
期刊：
影响因子：
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通讯作者：
Langmead,Ben
中科院分区：
文献类型：
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作者：
Lin,Mao-Jan;Iyer,Sheila;Chen,Nae-Chyun;Langmead,Ben
许多生物信息学方法试图减少参考偏差，但不存在全面测量参考偏差的方法。Biastools 对参考偏差的实例进行分析和分类。它适用于各种场景：当已知供体的变体并模拟读数时；当供体变异已知且读数真实时；当变异未知且读数真实时。使用biastools，我们观察到更具包容性的图基因组会导致有偏见的位点更少。我们发现，相对于局部对齐器，端到端对齐减少了插入缺失的偏差。最后，我们使用偏差工具来描述 T2T 参考如何改善大规模偏差。
Many bioinformatics methods seek to reduce reference bias, but no methods exist to comprehensively measure it.Biastoolsanalyzes 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. Usingbiastools, 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 usebiastoolsto characterize how T2T references improve large-scale bias.