Literature DB >> 36242770

Multiomics data integration to reveal chromatin remodeling and reorganization induced by gene mutational synergy.

Haiyang Yun1, Shabana Vohra2, David Lara-Astiaso2, Brian J P Huntly3.   

Abstract

Recurrent gene mutations often cooperate in a predefined stepwise and synergistic manner to alter global transcription, through directly or indirectly remodeling epigenetic landscape on linear and three-dimensional (3D) scales. Here, we present a multiomics data integration approach to investigate the impact of gene mutational synergy on transcription, chromatin states, and 3D chromatin organization in a murine leukemia model. This protocol provides an executable framework to study epigenetic remodeling induced by cooperating gene mutations and to identify the critical regulatory network involved. For complete details on the use and execution of this protocol, please refer to Yun et al. (2021).
Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Bioinformatics; Cancer; Genomics

Year:  2022        PMID: 36242770      PMCID: PMC9579702          DOI: 10.1016/j.xpro.2022.101770

Source DB:  PubMed          Journal:  STAR Protoc        ISSN: 2666-1667


  13 in total

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Journal:  Cell Rep       Date:  2020-04-21       Impact factor: 9.423

2.  featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

Authors:  Yang Liao; Gordon K Smyth; Wei Shi
Journal:  Bioinformatics       Date:  2013-11-13       Impact factor: 6.937

3.  STAR: ultrafast universal RNA-seq aligner.

Authors:  Alexander Dobin; Carrie A Davis; Felix Schlesinger; Jorg Drenkow; Chris Zaleski; Sonali Jha; Philippe Batut; Mark Chaisson; Thomas R Gingeras
Journal:  Bioinformatics       Date:  2012-10-25       Impact factor: 6.937

4.  ShinyGO: a graphical gene-set enrichment tool for animals and plants.

Authors:  Steven Xijin Ge; Dongmin Jung; Runan Yao
Journal:  Bioinformatics       Date:  2020-04-15       Impact factor: 6.937

5.  Differential oestrogen receptor binding is associated with clinical outcome in breast cancer.

Authors:  Caryn S Ross-Innes; Rory Stark; Andrew E Teschendorff; Kelly A Holmes; H Raza Ali; Mark J Dunning; Gordon D Brown; Ondrej Gojis; Ian O Ellis; Andrew R Green; Simak Ali; Suet-Feung Chin; Carlo Palmieri; Carlos Caldas; Jason S Carroll
Journal:  Nature       Date:  2012-01-04       Impact factor: 49.962

6.  Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.

Authors:  Michael I Love; Wolfgang Huber; Simon Anders
Journal:  Genome Biol       Date:  2014       Impact factor: 13.583

7.  HTSeq--a Python framework to work with high-throughput sequencing data.

Authors:  Simon Anders; Paul Theodor Pyl; Wolfgang Huber
Journal:  Bioinformatics       Date:  2014-09-25       Impact factor: 6.937

8.  CHiCAGO: robust detection of DNA looping interactions in Capture Hi-C data.

Authors:  Jonathan Cairns; Paula Freire-Pritchett; Steven W Wingett; Csilla Várnai; Andrew Dimond; Vincent Plagnol; Daniel Zerbino; Stefan Schoenfelder; Biola-Maria Javierre; Cameron Osborne; Peter Fraser; Mikhail Spivakov
Journal:  Genome Biol       Date:  2016-06-15       Impact factor: 13.583

9.  Model-based analysis of ChIP-Seq (MACS).

Authors:  Yong Zhang; Tao Liu; Clifford A Meyer; Jérôme Eeckhoute; David S Johnson; Bradley E Bernstein; Chad Nusbaum; Richard M Myers; Myles Brown; Wei Li; X Shirley Liu
Journal:  Genome Biol       Date:  2008-09-17       Impact factor: 13.583

10.  HiCUP: pipeline for mapping and processing Hi-C data.

Authors:  Steven Wingett; Philip Ewels; Mayra Furlan-Magaril; Takashi Nagano; Stefan Schoenfelder; Peter Fraser; Simon Andrews
Journal:  F1000Res       Date:  2015-11-20
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