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. 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

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English (US)
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 - Jan 1 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

Other

Other	2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014
Country/Territory	United States
City	Atlanta, GA
Period	7/13/14 → 7/18/14

Keywords

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

ASJC Scopus subject areas

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

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10.1145/2616498.2616513

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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.

Proceedings of the XSEDE 2014 Conference: Engaging Communities. Association for Computing Machinery, 2014. 7.

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

Yin, Z , Li, F & Wong, ST 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, Association for Computing Machinery, 2014 Annual Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2014, Atlanta, GA, United States, 7/13/14. https://doi.org/10.1145/2616498.2616513

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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, Reversible jump markov chain monte carlo, RNAi, Texas advanced computing center",

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doi = "10.1145/2616498.2616513",

language = "English (US)",

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N2 - 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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An integrated analytic pipeline for identifying and predicting genetic interactions based on perturbation data from high content double RNAi screening

Abstract

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Keywords

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