The NetRep paper has now been published in Cell Systems! Led by PhD student Scott Ritchie, this was an exciting collaboration of the Inouye, Abraham, and Holt labs.
Ritchie SC, Watts S, Fearnley LG, Holt KE, Abraham G, Inouye M. A scalable permutation approach reveals replication and preservation patterns of network modules in large datasets. Cell Systems 2016. 3(1):71-82.
The NetRep software has been certified by software testers at Cell Systems and is available here.
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.