Literature DB >> 30010788

Determination of sets of covariating gene expression using graph analysis on pairwise expression ratios.

Emmanuel Curis1,2,3, Cindie Courtin2, Pierre Alexis Geoffroy2,4, Jean-Louis Laplanche2, Bruno Saubaméa2, Cynthia Marie-Claire2.   

Abstract

Motivation: RNA quantification experiments result in compositional data, however usual methods for compositional data analysis [additive log ratio (alr), centered log ratio (clr), isometric log ratio (ilr)] do not apply easily and give results difficult to interpret. To handle this, a method based on disjoint subgraphs in a graph whose nodes are the quantified RNAs is proposed. Edges in the graph are defined by lack of change in ratios of the corresponding RNAs between conditions.
Results: The methods is suited for qRT-PCR and RNA-Seq data analyses, and leads to easy-to-interpret, graphical results and the identification of set of genes that share a similar behavior when the studied condition changes. For qRT-PCR data, it has better statistical properties than the common ΔΔCq method. Availability and implementation: Construction of all pairwise ratio analysis P-values matrix, and conversion into a graph was implemented in an R package, named SARP.compo. It is freely available for download on the CRAN repository. Example R script using the package are provided as Supplementary Material; the R package includes the data needed. One of these scripts reproduces the Figure 2 of this paper. Supplementary information: Supplementary data are available at Bioinformatics online.

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Year:  2019        PMID: 30010788     DOI: 10.1093/bioinformatics/bty629

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

1.  Selecting reference genes in RT-qPCR based on equivalence tests: a network based approach.

Authors:  Emmanuel Curis; Calypso Nepost; Diane Grillault Laroche; Cindie Courtin; Jean-Louis Laplanche; Bruno Etain; Cynthia Marie-Claire
Journal:  Sci Rep       Date:  2019-11-07       Impact factor: 4.379

2.  Both simulation and sequencing data reveal coinfections with multiple SARS-CoV-2 variants in the COVID-19 pandemic.

Authors:  Yinhu Li; Yiqi Jiang; Zhengtu Li; Yonghan Yu; Jiaxing Chen; Wenlong Jia; Yen Kaow Ng; Feng Ye; Shuai Cheng Li; Bairong Shen
Journal:  Comput Struct Biotechnol J       Date:  2022-03-18       Impact factor: 7.271

3.  Individual differences in cocaine-induced conditioned place preference in male rats: Behavioral and transcriptomic evidence.

Authors:  Luisa Alessandra Atehortua Martinez; Emmanuel Curis; Nawel Mekdad; Claire Larrieu; Cindie Courtin; Laurent Jourdren; Corinne Blugeon; Jean-Louis Laplanche; Bruno Megarbane; Cynthia Marie-Claire; Nadia Benturquia
Journal:  J Psychopharmacol       Date:  2022-09-19       Impact factor: 4.562

4.  Metabolomics analysis of human acute graft-versus-host disease reveals changes in host and microbiota-derived metabolites.

Authors:  David Michonneau; Eleonora Latis; Emmanuel Curis; Laetitia Dubouchet; Sivapriya Ramamoorthy; Brian Ingram; Régis Peffault de Latour; Marie Robin; Flore Sicre de Fontbrune; Sylvie Chevret; Lars Rogge; Gérard Socié
Journal:  Nat Commun       Date:  2019-12-13       Impact factor: 14.919

5.  In utero human intestine harbors unique metabolome, including bacterial metabolites.

Authors:  Yujia Li; Jessica M Toothaker; Shira Ben-Simon; Lital Ozeri; Ron Schweitzer; Blake T McCourt; Collin C McCourt; Lael Werner; Scott B Snapper; Dror S Shouval; Soliman Khatib; Omry Koren; Sameer Agnihorti; George Tseng; Liza Konnikova
Journal:  JCI Insight       Date:  2020-11-05
  5 in total

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