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GSKB: A gene set database for pathway analysis in mouse

Liming Lai, Jason Hennessey, Valerie Bares, Eun Woo Son, Yuguang Ban, Wei Wang, Jianli Qi, Gaixin Jiang, Arthur Liberzon, View ORCID ProfileSteven Xijin Ge
doi: https://doi.org/10.1101/082511
Liming Lai
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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Jason Hennessey
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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Valerie Bares
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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Eun Woo Son
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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Yuguang Ban
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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Wei Wang
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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Jianli Qi
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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Gaixin Jiang
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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Arthur Liberzon
2Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
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Steven Xijin Ge
1Department of Mathematics and Statistics, South Dakota State University, Brookings, SD 57007, USA
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  • ORCID record for Steven Xijin Ge
  • For correspondence: gexijin@gmail.com
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ABSTRACT

Interpretation of high-throughput genomics data based on biological pathways constitutes a constant challenge, partly because of the lack of supporting pathway database. In this study, we created a functional genomics knowledgebase in mouse, which includes 33,261 pathways and gene sets compiled from 40 sources such as Gene Ontology, KEGG, GeneSetDB, PANTHER, microRNA and transcription factor target genes, etc. In addition, we also manually collected and curated 8,747 lists of differentially expressed genes from 2,526 published gene expression studies to enable the detection of similarity to previously reported gene expression signatures. These two types of data constitute a Gene Set Knowledgebase (GSKB), which can be readily used by various pathway analysis software such as gene set enrichment analysis (GSEA). Using our knowledgebase, we were able to detect the correct microRNA (miR-29) pathway that was suppressed using antisense oligonucleotides and confirmed its role in inhibiting fibrogenesis, which might involve upregulation of transcription factor SMAD3. The knowledgebase can be queried as a source of published gene lists for further meta-analysis. Through meta-analysis of 56 published gene lists related to retina cells, we revealed two fundamentally different types of gene expression changes. One is related to stress and inflammatory response blamed for causing blindness in many diseases; the other associated with visual perception by normal retina cells. GSKB is available online at http://ge-lab.org/gs/, and also as a Bioconductor package (gskb, https://bioconductor.org/packages/gskb/). This database enables in-depth interpretation of mouse genomics data both in terms of known pathways and the context of thousands of published expression signatures.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted October 24, 2016.
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GSKB: A gene set database for pathway analysis in mouse
Liming Lai, Jason Hennessey, Valerie Bares, Eun Woo Son, Yuguang Ban, Wei Wang, Jianli Qi, Gaixin Jiang, Arthur Liberzon, Steven Xijin Ge
bioRxiv 082511; doi: https://doi.org/10.1101/082511
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GSKB: A gene set database for pathway analysis in mouse
Liming Lai, Jason Hennessey, Valerie Bares, Eun Woo Son, Yuguang Ban, Wei Wang, Jianli Qi, Gaixin Jiang, Arthur Liberzon, Steven Xijin Ge
bioRxiv 082511; doi: https://doi.org/10.1101/082511

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