Scoring overlapping and adjacent signals from genome-wide ChIP and DamID assays.
Scoring overlapping and adjacent signals from genome-wide ChIP and DamID assays.
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DOI：
10.1039/b906880e
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发表时间：
2009-12
影响因子：
--
通讯作者：
Adryan B
中科院分区：
文献类型：
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作者：
Fu AQ;Adryan B
许多利用全基因组芯片和DamID分析的研究旨在了解转录因子结合和染色质修饰密码的组合特征。随着这些实验方法变得更加负担得起和广泛使用，研究的重点正转向理解数据。在数据分析产生的许多挑战中，我们关心的是使用CHIP和DAMID分析产生的全基因组图谱来识别具有生物学意义的转录因子结合或染色质修饰的共现。共现反映在多个芯片或DamID配置文件中的重叠和相邻信号中。我们回顾了现有的定量方法来对芯片和DamID图谱中的重叠和结合事件进行评分和聚类。对于配对比较，现有的方法要么基于基因组水平的单一分数，要么采取基因组、区域特定的观点。为了同时从多个图谱中得出推论，存在根据区域的调控重要性对区域进行分类或推断特定区域的顺式调控模块的方法。我们提供了这些方法使用的一些统计工具的简单指南。
Much of the research utilising genome-wide ChIP and DamID assays aims to understand the combinatorial feature of transcription factor binding and the chromatin modification code.With these experimental methods becoming more affordable and widespread, the focus of research is shifting to making sense of the data. Amongst the many challenges arising from data analyses, we are concerned with identifying biologically meaningful co-occurrences of transcription factor binding or chromatin modifications, using genome-wide profiles generated from ChIP and DamID assays. Co-occurrences are reflected in overlapping and adjacent signals in multiple ChIP or DamID profiles. We review existing quantitative methods to score overlaps and to cluster binding events in ChIP and DamID profiles. For pairwise comparison, existing methods either are based on a single score at the genome level or take a genomic, region-specific view. To draw inference from many profiles simultaneously, methods exist to cluster regions by their regulatory importance or to infer cis-regulatory modules for a particular region. We provide a simple guide to some of the statistical tools used by these methods.