TY - JOUR
T1 - A Scalable Permutation Approach Reveals Replication and Preservation Patterns of Network Modules in Large Datasets
AU - Ritchie, Scott C.
AU - Watts, Stephen
AU - Fearnley, Liam G.
AU - Holt, Kathryn E.
AU - Abraham, Gad
AU - Inouye, Michael
PY - 2016/7/27
Y1 - 2016/7/27
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84995528886&partnerID=8YFLogxK
U2 - 10.1016/j.cels.2016.06.012
DO - 10.1016/j.cels.2016.06.012
M3 - Article
C2 - 27467248
AN - SCOPUS:84995528886
SN - 2405-4712
VL - 3
SP - 71
EP - 82
JO - Cell Systems
JF - Cell Systems
IS - 1
ER -