motifbreakR v2: expanded variant analysis including indels and integrated evidence from transcription factor binding databases.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2024-10-23 eCollection Date: 2024-01-01 DOI:10.1093/bioadv/vbae162
Simon G Coetzee, Dennis J Hazelett
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引用次数: 0

Abstract

Motivation: motifbreakR scans genetic variants against position weight matrices of transcription factors (TFs) to determine the potential for the disruption of binding at the site of the variant. It leverages the Bioconductor suite of software packages and annotations to query a diverse array of genomes and motif databases. Initially developed to interrogate the effect of single-nucleotide variants on TF binding sites, in motifbreakR v2, we have updated the functionality.

Results: New features include the ability to query other types of complex genetic variants, such as short insertions and deletions. This capability allows modeling a more extensive array of variants that may have significant effects on TF binding. Additionally, predictions based on sequence preference alone can indicate many more potential binding events than observed. Adding information from DNA-binding sequencing datasets lends confidence to motif disruption prediction by demonstrating TF binding in cell lines and tissue types. Therefore, motifbreakR can directly query the ReMap2022 database for evidence that a TF matching the disrupted motif binds over the disrupting variant. Finally, in motifbreakR, in addition to the existing interface, we implemented an R/Shiny graphical user interface to simplify and enhance access to researchers with different skill sets.

Availability and implementation: motifbreakR is implemented in R. Source code, documentation, and tutorials are available on Bioconductor at https://bioconductor.org/packages/release/bioc/html/motifbreakR.html and GitHub at https://github.com/Simon-Coetzee/motifBreakR.

motifbreakR v2:扩展的变异分析,包括嵌合和来自转录因子结合数据库的综合证据。
动机:motifbreakR 可根据转录因子 (TF) 的位置权重矩阵扫描遗传变异,以确定在变异位点破坏结合的可能性。它利用 Bioconductor 软件包和注释来查询各种基因组和主题数据库。在 motifbreakR v2 中,我们更新了其功能:新功能包括能够查询其他类型的复杂遗传变异,如短插入和短缺失。这一功能允许对可能对 TF 结合产生重大影响的变异进行更广泛的建模。此外,仅根据序列偏好进行预测可能会显示出比观察到的更多的潜在结合事件。通过展示细胞系和组织类型中的 TF 结合情况,从 DNA 结合测序数据集中添加信息可增强对图案破坏预测的信心。因此,motifbreakR 可以直接查询 ReMap2022 数据库,以获得与中断基调匹配的 TF 与中断变体结合的证据。最后,在 motifbreakR 中,除了现有的界面外,我们还实现了一个 R/Shiny 图形用户界面,以简化和提高具有不同技能组合的研究人员的访问能力。源代码、文档和教程可在 Bioconductor https://bioconductor.org/packages/release/bioc/html/motifbreakR.html 和 GitHub https://github.com/Simon-Coetzee/motifBreakR 上获取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.60
自引率
0.00%
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