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

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Abstrakt

Tytuł:: Analysis of ChIP-Seq and RNA-Seq Data with BioWardrobe.
Autorzy:: Vallabh S; Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Kartashov AV; Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA.
Barski A; Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. .; Division of Human Genetics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA. .; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA. .
Źródło:: Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2018; Vol. 1783, pp. 343-360.
Typ publikacji:: Journal Article
Język:: English
Imprint Name(s):: Publication: Totowa, NJ : Humana Press
Original Publication: Clifton, N.J. : Humana Press,
MeSH Terms:: Transcriptome*
Chromatin Immunoprecipitation/*methods
Computational Biology/*methods
Gene Expression Profiling/*methods
High-Throughput Nucleotide Sequencing/*methods
Sequence Analysis, RNA/*methods
Chromatin/genetics ; Chromatin/metabolism ; DNA-Binding Proteins/metabolism ; Humans ; Quality Control ; Software
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Grant Information:: DP2 GM119134 United States GM NIGMS NIH HHS
Contributed Indexing:: Keywords: ATAC-Seq; ChIP-Seq; DNase-Seq; Epigenomics; Heatmaps; Next-generation sequencing; Peak calling; RNA-Seq; RPKM; Transcriptomics
Substance Nomenclature:: 0 (Chromatin)
0 (DNA-Binding Proteins)
Entry Date(s):: Date Created: 20180517 Date Completed: 20190222 Latest Revision: 20190222
Update Code:: 20240104
PubMed Central ID:: PMC6188658
DOI:: 10.1007/978-1-4939-7834-2_17
PMID:: 29767371
: Czasopismo naukowe

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.

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