signatureSearch: environment for gene expression signature searching and functional interpretation

Author:

Duan Yuzhu1,Evans Daniel S2,Miller Richard A3,Schork Nicholas J4,Cummings Steven R2,Girke Thomas1ORCID

Affiliation:

1. Institute for Integrative Genome Biology, 1207F Genomics Building, University of California, Riverside, CA 92521, USA

2. California Pacific Medical Center Research Institute, 550 16th Street, 2nd floor, San Francisco, CA 94158, USA

3. Department of Pathology, University of Michigan, Ann Arbor, MI 48109, USA

4. Department of Quantitative Medicine and Systems Biology, The Translational Genomics Research Institute, 445 N. Fifth Street Phoenix, AZ 85004, USA

Abstract

Abstract signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases.

Funder

National Institutes of Health

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Genetics

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