Addressing confounding artifacts in reconstruction of gene co-expression networks

Gene co-expression networks capture biological relationships between genes and are important tools in predicting gene function and understanding disease mechanisms. We show that technical and biological artifacts in gene expression data confound commonly used network reconstruction algorithms. We de...

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Vydáno v:	Genome Biology Ročník 20; číslo 1; s. 94
Hlavní autoři:	Parsana, Princy, Ruberman, Claire, Jaffe, Andrew E., Schatz, Michael C., Battle, Alexis, Leek, Jeffrey T.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 16.05.2019 Springer Nature B.V BMC
Témata:	algorithms Animal Genetics and Genomics Bias Bioinformatics Biomedical and Life Sciences Evolutionary Biology gene components Gene expression Gene Regulatory Networks Genetic Techniques Genomes Genomics Human Genetics Humans Life Sciences measurement Microbial Genetics and Genomics Plant Genetics and Genomics prediction Short Report Simulation Teaching methods tissues
ISSN:	1474-760X, 1474-7596, 1474-760X
On-line přístup:	Získat plný text
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Shrnutí:	Gene co-expression networks capture biological relationships between genes and are important tools in predicting gene function and understanding disease mechanisms. We show that technical and biological artifacts in gene expression data confound commonly used network reconstruction algorithms. We demonstrate theoretically, in simulation, and empirically, that principal component correction of gene expression measurements prior to network inference can reduce false discoveries. Using data from the GTEx project in multiple tissues, we show that this approach reduces false discoveries beyond correcting only for known confounders.
Bibliografie:	SourceType-Scholarly Journals-1 content type line 14 ObjectType-Report-1 ObjectType-Article-2 ObjectType-Undefined-1 ObjectType-Feature-3 content type line 23 ObjectType-Article-1 ObjectType-Feature-2
ISSN:	1474-760X 1474-7596 1474-760X
DOI:	10.1186/s13059-019-1700-9