RT Journal Article
SR Electronic
T1 The Signaling Pathways Project: an integrated ‘omics knowledgebase for mammalian cellular signaling pathways
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 401729
DO 10.1101/401729
A1 Scott Ochsner
A1 David Abraham
A1 Kirt Martin
A1 Wei Ding
A1 Apollo McOwiti
A1 Wasula Kankanamge
A1 Zichen Wang
A1 Kaitlyn Andreano
A1 Ross A. Hamilton
A1 Yue Chen
A1 Angelica Hamilton
A1 Marin L. Gantner
A1 Michael Dehart
A1 Shijing Qu
A1 Susan G. Hilsenbeck
A1 Lauren B. Becnel
A1 Dave Bridges
A1 Avi Ma’ayan
A1 Janice M. Huss
A1 Fabio Stossi
A1 Charles E. Foulds
A1 Anastasia Kralli
A1 Donald P. McDonnell
A1 Neil J. McKenna
YR 2019
UL http://biorxiv.org/content/early/2019/06/03/401729.abstract
AB Integrated mining of public transcriptomic and ChIP-Seq datasets has the potential to illuminate facets of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates stable community classifications of the four major categories of signaling pathway node (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules (BSMs). We then mapped over 10,000 public transcriptomic or cistromic experiments to their relevant signaling pathway node, BSM or biosample of study. To provide for prediction of pathway node-target transcriptional regulatory relationships, we generated consensus ‘omics signatures, or consensomes, based on measures of significant differential expression of genomic targets across all underlying transcriptomic experiments. To expose the SPP knowledgebase to researchers, a web browser interface accommodates a variety of routine data mining strategies. Consensomes were validated using alignment with literature-based knowledge, gene target-level integration of transcriptomic and ChIP-Seq data points, and in bench experiments that confirmed previously uncharacterized node-gene target regulatory relationships. SPP is freely accessible at https://beta.signalingpathways.org.