Using networks to measure similarity between genes: Association index selection

Juan I.Fuxman Bass, Alos Diallo, Justin Nelson, Juan M. Soto, Chad L. Myers, Albertha J.M. Walhout

Research output: Contribution to journalReview articlepeer-review

104 Scopus citations

Abstract

Biological networks can be used to functionally annotate genes on the basis of interaction-profile similarities. Metrics known as association indices can be used to quantify interaction-profile similarity. We provide an overview of commonly used association indices, including the Jaccard index and the Pearson correlation coefficient, and compare their performance in different types of analyses of biological networks. We introduce the Guide for Association Index for Networks (GAIN), a web tool for calculating and comparing interaction-profile similarities and defining modules of genes with similar profiles.

Original languageEnglish (US)
Pages (from-to)1169-1176
Number of pages8
JournalNature Methods
Volume10
Issue number12
DOIs
StatePublished - Dec 2013

Bibliographical note

Funding Information:
We thank members of A.J.M.W.’s lab, R. McCord and B. Lajoie for discussions and critical reading of the manuscript. We thank J.C. Bare (Institute of Systems Biology) for helpful advice in the development of GAIN. This work was supported by the US National Institutes of Health grants DK068429 and GM082971 to A.J.M.W. J.I.F.B. is partially supported by a postdoctoral fellowship from the Pew Latin American Fellows Program. J.N. and C.L.M. are partially supported by grant DBI-0953881 from the US National Science Foundation.

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