title: A Scalable Permutation Approach Reveals Replication and Preservation Patterns of Network Modules in Large Datasets.
abstract: Network modules-topologically distinct groups of edges and nodes-that are preserved across datasets can reveal common features of organisms, tissues, cell types, and molecules. Many statistics to identify such modules have been developed, but testing their significance requires heuristics. Here, we demonstrate that current methods for assessing module preservation are systematically biased and produce skewed p values. We introduce NetRep, a rapid and computationally efficient method that uses a permutation approach to score module preservation without assuming data are normally distributed. NetRep produces unbiased p values and can distinguish between true and false positives during multiple hypothesis testing. We use NetRep to quantify preservation of gene coexpression modules across murine brain, liver, adipose, and muscle tissues. Complex patterns of multi-tissue preservation were revealed, including a liver-derived housekeeping module that displayed adipose- and muscle-specific association with body weight. Finally, we demonstrate the broader applicability of NetRep by quantifying preservation of bacterial networks in gut microbiota between men and women.
authors.affiliation: Centre for Systems Genomics, The University of Melbourne, Parkville, VIC 3010, Australia; Department of Pathology, The University of Melbourne, Parkville, VIC 3010, Australia. Electronic address: scottr@student.unimelb.edu.au.
authors.forename: Scott C
authors.initials: SC
authors.lastname: Ritchie
authors.affiliation: Centre for Systems Genomics, The University of Melbourne, Parkville, VIC 3010, Australia; Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC 3010, Australia.
authors.forename: Stephen
authors.initials: S
authors.lastname: Watts
authors.affiliation: Centre for Systems Genomics, The University of Melbourne, Parkville, VIC 3010, Australia; Department of Pathology, The University of Melbourne, Parkville, VIC 3010, Australia; School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia.
authors.forename: Liam G
authors.initials: LG
authors.lastname: Fearnley
authors.affiliation: Centre for Systems Genomics, The University of Melbourne, Parkville, VIC 3010, Australia; Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, VIC 3010, Australia.
authors.forename: Kathryn E
authors.initials: KE
authors.lastname: Holt
authors.affiliation: Centre for Systems Genomics, The University of Melbourne, Parkville, VIC 3010, Australia; Department of Pathology, The University of Melbourne, Parkville, VIC 3010, Australia; School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia.
authors.forename: Gad
authors.initials: G
authors.lastname: Abraham
authors.affiliation: Centre for Systems Genomics, The University of Melbourne, Parkville, VIC 3010, Australia; Department of Pathology, The University of Melbourne, Parkville, VIC 3010, Australia; School of BioSciences, The University of Melbourne, Parkville, VIC 3010, Australia. Electronic address: minouye@unimelb.edu.au.
authors.forename: Michael
authors.initials: M
authors.lastname: Inouye
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain; D019295:Computational Biology; D004261:DNA Replication; D005260:Female; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D006801:Humans; D008297:Male; D051379:Mice; D009154:Mutation; D020411:Oligonucleotide Array Sequence Analysis