Literature DB >> 29767371

Analysis of ChIP-Seq and RNA-Seq Data with BioWardrobe.

Sushmitha Vallabh1, Andrey V Kartashov1, Artem Barski2,3,4.   

Abstract

The massive amount of information produced by ChIP-Seq, RNA-Seq, and other next-generation sequencing-based methods requires computational data analysis. However, biologists performing these experiments often lack training in bioinformatics. BioWardrobe aims to bridge this gap by providing a convenient user interface and by automating routine data-processing steps. This protocol details the use of BioWardrobe for identifying and visualizing ChIP-Seq peaks, calculating RPKMs, performing differential binding or gene expression analysis, and creating plots and heat maps. We specifically describe how to use BioWardrobe's quality control measures for troubleshooting NGS-based experiments.

Entities:  

Keywords:  ATAC-Seq; ChIP-Seq; DNase-Seq; Epigenomics; Heatmaps; Next-generation sequencing; Peak calling; RNA-Seq; RPKM; Transcriptomics

Mesh:

Substances:

Year:  2018        PMID: 29767371      PMCID: PMC6188658          DOI: 10.1007/978-1-4939-7834-2_17

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  19 in total

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2.  Mapping and quantifying mammalian transcriptomes by RNA-Seq.

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3.  Differential analysis of gene regulation at transcript resolution with RNA-seq.

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4.  Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing.

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Journal:  Nat Methods       Date:  2007-06-11       Impact factor: 28.547

5.  MAnorm: a robust model for quantitative comparison of ChIP-Seq data sets.

Authors:  Zhen Shao; Yijing Zhang; Guo-Cheng Yuan; Stuart H Orkin; David J Waxman
Journal:  Genome Biol       Date:  2012-03-16       Impact factor: 13.583

6.  Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences.

Authors:  Jeremy Goecks; Anton Nekrutenko; James Taylor
Journal:  Genome Biol       Date:  2010-08-25       Impact factor: 13.583

7.  MEME-ChIP: motif analysis of large DNA datasets.

Authors:  Philip Machanick; Timothy L Bailey
Journal:  Bioinformatics       Date:  2011-04-12       Impact factor: 6.937

8.  Differential expression analysis for sequence count data.

Authors:  Simon Anders; Wolfgang Huber
Journal:  Genome Biol       Date:  2010-10-27       Impact factor: 13.583

9.  TopHat: discovering splice junctions with RNA-Seq.

Authors:  Cole Trapnell; Lior Pachter; Steven L Salzberg
Journal:  Bioinformatics       Date:  2009-03-16       Impact factor: 6.937

10.  BioWardrobe: an integrated platform for analysis of epigenomics and transcriptomics data.

Authors:  Andrey V Kartashov; Artem Barski
Journal:  Genome Biol       Date:  2015-08-07       Impact factor: 13.583

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Journal:  G3 (Bethesda)       Date:  2019-03-07       Impact factor: 3.154

2.  CWL-Airflow: a lightweight pipeline manager supporting Common Workflow Language.

Authors:  Michael Kotliar; Andrey V Kartashov; Artem Barski
Journal:  Gigascience       Date:  2019-07-01       Impact factor: 6.524

3.  CAncer bioMarker Prediction Pipeline (CAMPP)-A standardized framework for the analysis of quantitative biological data.

Authors:  Thilde Terkelsen; Anders Krogh; Elena Papaleo
Journal:  PLoS Comput Biol       Date:  2020-03-16       Impact factor: 4.475

4.  FOXF1 is required for the oncogenic properties of PAX3-FOXO1 in rhabdomyosarcoma.

Authors:  David Milewski; Samriddhi Shukla; Berkley E Gryder; Arun Pradhan; Johnny Donovan; Parvathi Sudha; Sushmitha Vallabh; Athena Pyros; Yan Xu; Artem Barski; Sara Szabo; Brian Turpin; Joseph G Pressey; Douglas P Millay; Javed Khan; Vladimir V Kalinichenko; Tanya V Kalin
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Review 5.  Runx Transcription Factors in T Cells-What Is Beyond Thymic Development?

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6.  Bidirectional crosstalk between eosinophils and esophageal epithelial cells regulates inflammatory and remodeling processes.

Authors:  Julia L M Dunn; Julie M Caldwell; Adina Ballaban; Netali Ben-Baruch Morgenstern; Mark Rochman; Marc E Rothenberg
Journal:  Mucosal Immunol       Date:  2021-05-10       Impact factor: 7.313

  6 in total

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