Literature DB >> 35037216

Gene Co-expression Network Analysis.

Juan D Montenegro1.   

Abstract

Gene co-expression analysis is a data analysis technique that helps identify groups of genes with similar expression patterns across several different conditions. By means of these techniques, different groups have been able to assign putative metabolic pathways and functions to understudied genes and to identify novel metabolic regulation networks for different metabolites. Some groups have even used network comparative studies to understand the evolution of these networks from green algae to land plants. In this chapter, we will go over the basic definitions required to understand network topology and gene module identification. Additionally, we offer the reader a walk-through a standard analysis pipeline as implemented in the package WGCNA that takes as input raw fastq files and obtains co-expressed gene clusters and representative gene expression patterns from each module for downstream applications.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Eigengene; Free scale topology; Gene co-expression; Gene modules; RNA-seq; Topology overlap measurement

Mesh:

Year:  2022        PMID: 35037216     DOI: 10.1007/978-1-0716-2067-0_19

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


  40 in total

Review 1.  Plant GSTome: structure and functional role in xenome network and plant stress response.

Authors:  Nikolaos E Labrou; Anastassios C Papageorgiou; Ourania Pavli; Emmanouil Flemetakis
Journal:  Curr Opin Biotechnol       Date:  2015-01-19       Impact factor: 9.740

2.  A Global Coexpression Network Approach for Connecting Genes to Specialized Metabolic Pathways in Plants.

Authors:  Jennifer H Wisecaver; Alexander T Borowsky; Vered Tzin; Georg Jander; Daniel J Kliebenstein; Antonis Rokas
Journal:  Plant Cell       Date:  2017-04-13       Impact factor: 11.277

Review 3.  Transcriptional Regulatory Network of Plant Heat Stress Response.

Authors:  Naohiko Ohama; Hikaru Sato; Kazuo Shinozaki; Kazuko Yamaguchi-Shinozaki
Journal:  Trends Plant Sci       Date:  2016-09-22       Impact factor: 18.313

4.  Gene coexpression network analysis of oil biosynthesis in an interspecific backcross of oil palm.

Authors:  Chloé Guerin; Thierry Joët; Julien Serret; Philippe Lashermes; Virginie Vaissayre; Mawussé D T Agbessi; Thierry Beulé; Dany Severac; Philippe Amblard; James Tregear; Tristan Durand-Gasselin; Fabienne Morcillo; Stéphane Dussert
Journal:  Plant J       Date:  2016-07-19       Impact factor: 6.417

5.  Statistical Approaches for Gene Selection, Hub Gene Identification and Module Interaction in Gene Co-Expression Network Analysis: An Application to Aluminum Stress in Soybean (Glycine max L.).

Authors:  Samarendra Das; Prabina Kumar Meher; Anil Rai; Lal Mohan Bhar; Baidya Nath Mandal
Journal:  PLoS One       Date:  2017-01-05       Impact factor: 3.240

6.  Gene co-expression network analysis reveals coordinated regulation of three characteristic secondary biosynthetic pathways in tea plant (Camellia sinensis).

Authors:  Yuling Tai; Chun Liu; Shuwei Yu; Hua Yang; Jiameng Sun; Chunxiao Guo; Bei Huang; Zhaoye Liu; Yi Yuan; Enhua Xia; Chaoling Wei; Xiaochun Wan
Journal:  BMC Genomics       Date:  2018-08-15       Impact factor: 3.969

7.  WGCNA: an R package for weighted correlation network analysis.

Authors:  Peter Langfelder; Steve Horvath
Journal:  BMC Bioinformatics       Date:  2008-12-29       Impact factor: 3.169

8.  Connecting genes, coexpression modules, and molecular signatures to environmental stress phenotypes in plants.

Authors:  David J Weston; Lee E Gunter; Alistair Rogers; Stan D Wullschleger
Journal:  BMC Syst Biol       Date:  2008-02-04

9.  Co-expression network analysis reveals transcription factors associated to cell wall biosynthesis in sugarcane.

Authors:  Savio Siqueira Ferreira; Carlos Takeshi Hotta; Viviane Guzzo de Carli Poelking; Debora Chaves Coelho Leite; Marcos Silveira Buckeridge; Marcelo Ehlers Loureiro; Marcio Henrique Pereira Barbosa; Monalisa Sampaio Carneiro; Glaucia Mendes Souza
Journal:  Plant Mol Biol       Date:  2016-01-28       Impact factor: 4.076

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