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CrossFilt:一种跨物种过滤工具,可消除比较基因组学研究中的比对偏差。

CrossFilt: A Cross-species Filtering Tool that Eliminates Alignment Bias in Comparative Genomics Studies.

作者信息

Barr Kenneth A, Gilad Yoav

机构信息

Department of Medicine, University of Chicago; Chicago, IL 60637, USA.

Department of Human Genetics, University of Chicago; Chicago, IL 60637, USA.

出版信息

bioRxiv. 2025 Jun 6:2025.06.05.654938. doi: 10.1101/2025.06.05.654938.

Abstract

Comparative functional genomic studies are often affected by biased read mapping across species due to inter-species differences in genome structure, sequence composition, and annotation quality. We developed CrossFilt, a filtering strategy that retains only sequencing reads that map reciprocally between genomes, ensuring that quantification of read counts is based on directly comparable genomic features. Using both real and simulated RNA-sequencing data from primates, we show that CrossFilt outperforms five alternative approaches that are commonly used, resulting in more accurate inference of gene expression differences. Our results highlight the impact of preprocessing strategies on the analysis of cross-species functional genomics data.

摘要

由于物种间基因组结构、序列组成和注释质量存在差异,比较功能基因组学研究常常受到跨物种读段映射偏差的影响。我们开发了CrossFilt,这是一种过滤策略,仅保留能在基因组之间相互映射的测序读段,确保读段计数的定量基于直接可比的基因组特征。使用来自灵长类动物的真实和模拟RNA测序数据,我们表明CrossFilt优于五种常用的替代方法,能更准确地推断基因表达差异。我们的结果突出了预处理策略对跨物种功能基因组学数据分析的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/723b/12157504/fd7587a11a28/nihpp-2025.06.05.654938v1-f0001.jpg

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