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Construction and Optimization of a Large Gene Coexpression Network in Maize Using RNA-Seq Data.

Title: Construction and Optimization of a Large Gene Coexpression Network in Maize Using RNA-Seq Data.
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Name(s): Huang, Ji, author
Vendramin, Stefania, author
Shi, Lizhen, author
McGinnis, Karen M, author
Type of Resource: text
Genre: Journal Article
Text
Date Issued: 2017-09-01
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: With the emergence of massively parallel sequencing, genomewide expression data production has reached an unprecedented level. This abundance of data has greatly facilitated maize research, but may not be amenable to traditional analysis techniques that were optimized for other data types. Using publicly available data, a gene coexpression network (GCN) can be constructed and used for gene function prediction, candidate gene selection, and improving understanding of regulatory pathways. Several GCN studies have been done in maize (), mostly using microarray datasets. To build an optimal GCN from plant materials RNA-Seq data, parameters for expression data normalization and network inference were evaluated. A comprehensive evaluation of these two parameters and a ranked aggregation strategy on network performance, using libraries from 1266 maize samples, were conducted. Three normalization methods and 10 inference methods, including six correlation and four mutual information methods, were tested. The three normalization methods had very similar performance. For network inference, correlation methods performed better than mutual information methods at some genes. Increasing sample size also had a positive effect on GCN. Aggregating single networks together resulted in improved performance compared to single networks.
Identifier: FSU_pmch_28768814 (IID), 10.1104/pp.17.00825 (DOI), PMC5580776 (PMCID), 28768814 (RID), 28768814 (EID), pp.17.00825 (PII)
Publication Note: This NIH-funded author manuscript originally appeared in PubMed Central at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5580776.
Subject(s): Algorithms
Datasets as Topic
Gene Expression Profiling/methods
Gene Regulatory Networks
Oligonucleotide Array Sequence Analysis
RNA, Plant/chemistry
RNA, Plant/genetics
Sequence Analysis, RNA/methods
Zea mays/genetics
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_pmch_28768814
Owner Institution: FSU
Is Part Of: Plant physiology.
1532-2548
Issue: iss. 1, vol. 175

Choose the citation style.
Huang, J., Vendramin, S., Shi, L., & McGinnis, K. M. (2017). Construction and Optimization of a Large Gene Coexpression Network in Maize Using RNA-Seq Data. Plant Physiology. Retrieved from http://purl.flvc.org/fsu/fd/FSU_pmch_28768814