Yingying Cao1, Simo Kitanovski2, Daniel Hoffmann2. 1. Bioinformatics and Computational Biophysics, Faculty of Biology and Center for Medical Biotechnology (ZMB), University of Duisburg-Essen, Universitätsstr.2, Essen, 45141, Germany. yingying.cao@uni-due.de. 2. Bioinformatics and Computational Biophysics, Faculty of Biology and Center for Medical Biotechnology (ZMB), University of Duisburg-Essen, Universitätsstr.2, Essen, 45141, Germany.
Abstract
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.
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.
Authors: José J Fuster; Susan MacLauchlan; María A Zuriaga; Maya N Polackal; Allison C Ostriker; Raja Chakraborty; Chia-Ling Wu; Soichi Sano; Sujatha Muralidharan; Cristina Rius; Jacqueline Vuong; Sophia Jacob; Varsha Muralidhar; Avril A B Robertson; Matthew A Cooper; Vicente Andrés; Karen K Hirschi; Kathleen A Martin; Kenneth Walsh Journal: Science Date: 2017-01-19 Impact factor: 47.728
Authors: Yiyao Jiang; Xu Zhang; Ting Wei; Xianjie Qi; Isah Amir Abba; Nana Zhang; Yao Chen; Ran Wang; Chao Shi Journal: Front Cardiovasc Med Date: 2022-07-01