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

doi:10.1145/2616498.2616513

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 proceeding › Conference contribution › peer-review

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 language	English
Title of host publication	Proceedings of the XSEDE 2014 Conference
Subtitle of host publication	Engaging Communities
Publisher	Association for Computing Machinery
ISBN (Print)	9781450328937
DOIs	https://doi.org/10.1145/2616498.2616513
State	Published - 2014
Event	2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014 - Atlanta, GA, United States Duration: Jul 13 2014 → Jul 18 2014

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014
Country/Territory	United States
City	Atlanta, GA
Period	07/13/14 → 07/18/14

Keywords

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

Access to Document

10.1145/2616498.2616513

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 Article 7 (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/2616498.2616513

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

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].",

keywords = "Cell morphogenesis, High content screening, Perturbation response, RNAi, Reversible jump markov chain monte carlo, Texas advanced computing center",

author = "Zheng Yin and Fuhai Li and Wong, {Stephen T.C.}",

year = "2014",

doi = "10.1145/2616498.2616513",

language = "English",

isbn = "9781450328937",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

booktitle = "Proceedings of the XSEDE 2014 Conference",

note = "2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014 ; Conference date: 13-07-2014 Through 18-07-2014",

}

Yin, Z, Li, F & Wong, STC 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, 2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014, Atlanta, GA, United States, 07/13/14. https://doi.org/10.1145/2616498.2616513

An integrated analytic pipeline for identifying and predicting genetic interactions based on perturbation data from high content double RNAi screening. / Yin, Zheng; Li, Fuhai; Wong, Stephen T.C.
Proceedings of the XSEDE 2014 Conference: Engaging Communities. Association for Computing Machinery, 2014. 7 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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].

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KW - High content screening

KW - Perturbation response

KW - RNAi

KW - Reversible jump markov chain monte carlo

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

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