Deciphering cis-regulatory elements using REgulamentary

doi:10.1093/bioadv/vbag079

2026-01-01

PRE

Jennifer Clara Herrmann

Matthew Baxter

J.R. Hughes *

DOI：10.1093/bioadv/vbag079

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摘要

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全基因组关联研究揭示了多种与疾病相关的遗传变异位于基因组非编码区域。为优先考虑这些变异并阐明其功能作用，准确分类顺式调控元件至关重要。早期方法依赖特征组蛋白标记，而较新的方法使用隐马尔可夫模型将基因组分割为染色质状态。然而，这些模型常产生需要手动解释才能分配调控功能的抽象状态。REgulamentary被引入为一种基于规则的框架，用于特定细胞类型下从头、全基因组注释顺式调控元件。其行为与基于计数和分割的方法进行比较，以突出分类策略的差异和基于规则设计的可解释性优势。最后，通过应用于已发表的遗传关联数据来优先考虑可能的因果变异，展示了其在复杂疾病位点分析中的实用性。可用性与实现：REgulamentary使用Python实现，并采用基于Snakemake的工作流程进行可重复分析，整合了标准生物信息学工具。该软件可在以下地址获取：https://github.com/Genome-Function-Initiative-Oxford/REgulamentary

Keyword:

GENE-EXPRESSION

CHROMATIN

ENHANCERS

期刊

Bioinformatics Advances

IF:

2.8

论文数:

131

被引数:

机构

university of oxford

学者数:

9.8W

论文数: 8.6W

被引数: 137

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