CompMap:基于竞争映射的等位基因特异性表达式读取计数器。

microPublication biology Pub Date : 2025-06-02 eCollection Date: 2025-01-01 DOI:10.17912/micropub.biology.001599
Santiago Sanchez-Ramirez, Asher Cutter
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引用次数: 0

摘要

基因调控变化作用于顺式和反式基因可以推断等位基因特异性表达(ASE)转录组从种间和群体间杂交和他们的亲本。然而,映射偏差和过多信息丢失的问题可能会在繁琐的分析管道中无意中出现。我们介绍了CompMap,这是Python中的一个自包含方法,可以从基因型特异性比对中生成等位基因特异性表达计数。CompMap通过将读取映射统计数据与同源区域内的亲代比对进行比较,对读取进行排序和计数,而不仅仅是snp。不明确的比对按比例解决等位基因特异性计数或统计上使用二项分布。用CompMap进行的模拟表明,在评估监管分歧时错误率很低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CompMap: an allele-specific expression read counter based on competitive mapping.

Gene regulatory changes acting cis and trans to a gene can be inferred with allele-specific expression (ASE) transcriptomes from interspecies and inter-population hybrids and their parents. Problems of mapping bias and excessive information loss, however, can arise unintentionally from cumbersome analysis pipelines. We introduce CompMap, a self-contained method in Python that generates allele-specific expression counts from genotype-specific alignments. CompMap sorts and counts reads, not just SNPs, by comparing read-mapping statistics to parental alignments within homologous regions. Ambiguous alignments resolve proportionally to allele-specific counts or statistically using a binomial distribution. Simulations with CompMap show low error rates in assessing regulatory divergence.

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