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Tytuł pozycji:

intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data.

Tytuł:
intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data.
Autorzy:
Cao Y; Bioinformatics and Computational Biophysics, Faculty of Biology and Center for Medical Biotechnology (ZMB), University of Duisburg-Essen, Universitätsstr.2, Essen, 45141, Germany. .
Kitanovski S; Bioinformatics and Computational Biophysics, Faculty of Biology and Center for Medical Biotechnology (ZMB), University of Duisburg-Essen, Universitätsstr.2, Essen, 45141, Germany.
Hoffmann D; Bioinformatics and Computational Biophysics, Faculty of Biology and Center for Medical Biotechnology (ZMB), University of Duisburg-Essen, Universitätsstr.2, Essen, 45141, Germany.
Źródło:
BMC genomics [BMC Genomics] 2020 Dec 29; Vol. 21 (Suppl 11), pp. 802. Date of Electronic Publication: 2020 Dec 29.
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Original Publication: London : BioMed Central, [2000-
MeSH Terms:
Chromatin Immunoprecipitation Sequencing*
High-Throughput Nucleotide Sequencing*
Chromatin Immunoprecipitation ; Computational Biology ; RNA-Seq
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Grant Information:
HO 1582/12-1 Deutsche Forschungsgemeinschaft
Contributed Indexing:
Keywords: ChIP-Seq; Integrative analysis; RNA-Seq
Entry Date(s):
Date Created: 20201229 Date Completed: 20210514 Latest Revision: 20210514
Update Code:
20240105
PubMed Central ID:
PMC7771091
DOI:
10.1186/s12864-020-07205-6
PMID:
33372591
Czasopismo naukowe
Background: RNA-Seq, the high-throughput sequencing (HT-Seq) of mRNAs, has become an essential tool for characterizing gene expression differences between different cell types and conditions. Gene expression is regulated by several mechanisms, including epigenetically by post-translational histone modifications which can be assessed by ChIP-Seq (Chromatin Immuno-Precipitation Sequencing). As more and more biological samples are analyzed by the combination of ChIP-Seq and RNA-Seq, the integrated analysis of the corresponding data sets becomes, theoretically, a unique option to study gene regulation. However, technically such analyses are still in their infancy.
Results: Here we introduce intePareto, a computational tool for the integrative analysis of RNA-Seq and ChIP-Seq data. With intePareto we match RNA-Seq and ChIP-Seq data at the level of genes, perform differential expression analysis between biological conditions, and prioritize genes with consistent changes in RNA-Seq and ChIP-Seq data using Pareto optimization.
Conclusion: intePareto facilitates comprehensive understanding of high dimensional transcriptomic and epigenomic data. Its superiority to a naive differential gene expression analysis with RNA-Seq and available integrative approach is demonstrated by analyzing a public dataset.
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