An integrated analytic pipeline for identifying and predicting genetic interactions based on perturbation data from high content double RNAi screening

Zheng Yin, Fuhai Li, Stephen T.C. Wong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we describe an integrated data analysis pipeline for identifying and predicting genetic interactions based on cellular responses to perturbations of single-And multiple-Agents. This pipeline was developed in the context of genome wide single-RNAi screens and smaller scale double-RNAi screens using Drosophila KC-167 cell lines, with the aim to reconstruct the molecular pathways regulating changes in cell shape. The TACC (Texas Advanced Computing Center) under XSEDE framework allocated 100,000 service unites (SUs) from its Stampede system to facilitate image quantification and signaling pathway modeling using fluorescence images of Drosophila cells, and recently a kinome-wide single RNAi screening has been reported [1].

Original languageEnglish
Title of host publicationProceedings of the XSEDE 2014 Conference
Subtitle of host publicationEngaging Communities
PublisherAssociation for Computing Machinery
ISBN (Print)9781450328937
DOIs
StatePublished - Jan 1 2014
Externally publishedYes
Event2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014 - Atlanta, GA, United States
Duration: Jul 13 2014Jul 18 2014

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014
CountryUnited States
CityAtlanta, GA
Period07/13/1407/18/14

Keywords

  • Cell morphogenesis
  • High content screening
  • Perturbation response
  • RNAi
  • Reversible jump markov chain monte carlo
  • Texas advanced computing center

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  • Cite this

    Yin, Z., Li, F., & Wong, S. T. C. (2014). An integrated analytic pipeline for identifying and predicting genetic interactions based on perturbation data from high content double RNAi screening. In Proceedings of the XSEDE 2014 Conference: Engaging Communities [7] (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/2616498.2616513