Fast detection of differential chromatin domains with SCIDDO

Author:

Ebert Peter12ORCID,Schulz Marcel H2345ORCID

Affiliation:

1. Institute for Medical Biometry and Bioinformatics, Heinrich Heine University, 40225 Düsseldorf, Germany

2. Max Planck Institute for Informatics, Saarland Informatics Campus, 66123 Saarbrücken, Germany

3. Cluster of Excellence on Multimodal Computing and Interaction, Saarland Informatics Campus, 66123 Saarbrücken, Germany

4. Institute for Cardiovascular Regeneration, Goethe University, 60590 Frankfurt am Main, Germany

5. German Center for Cardiovascular Research (DZHK), Partner site Rhein-Main, 60590 Frankfurt am Main, Germany

Abstract

Abstract Motivation The generation of genome-wide maps of histone modifications using chromatin immunoprecipitation sequencing is a standard approach to dissect the complexity of the epigenome. Interpretation and differential analysis of histone datasets remains challenging due to regulatory meaningful co-occurrences of histone marks and their difference in genomic spread. To ease interpretation, chromatin state segmentation maps are a commonly employed abstraction combining individual histone marks. We developed the tool SCIDDO as a fast, flexible and statistically sound method for the differential analysis of chromatin state segmentation maps. Results We demonstrate the utility of SCIDDO in a comparative analysis that identifies differential chromatin domains (DCD) in various regulatory contexts and with only moderate computational resources. We show that the identified DCDs correlate well with observed changes in gene expression and can recover a substantial number of differentially expressed genes (DEGs). We showcase SCIDDO’s ability to directly interrogate chromatin dynamics, such as enhancer switches in downstream analysis, which simplifies exploring specific questions about regulatory changes in chromatin. By comparing SCIDDO to competing methods, we provide evidence that SCIDDO’s performance in identifying DEGs via differential chromatin marking is more stable across a range of cell-type comparisons and parameter cut-offs. Availability and implementation The SCIDDO source code is openly available under github.com/ptrebert/sciddo. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

German Epigenome Project (DEEP

German Science Ministry

DFG Clusters of Excellence on Multimodal Computing and Interaction

Cardio Pulmonary Institute

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3