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SbacHTS: spatial background noise correction for high-throughput RNAi screening.


ABSTRACT:

Motivation

High-throughput cell-based phenotypic screening has become an increasingly important technology for discovering new drug targets and assigning gene functions. Such experiments use hundreds of 96-well or 384-well plates, to cover whole-genome RNAi collections and/or chemical compound files, and often collect measurements that are sensitive to spatial background noise whose patterns can vary across individual plates. Correcting these position effects can substantially improve measurement accuracy and screening success.

Result

We developed SbacHTS (Spatial background noise correction for High-Throughput RNAi Screening) software for visualization, estimation and correction of spatial background noise in high-throughput RNAi screens. SbacHTS is supported on the Galaxy open-source framework with a user-friendly open access web interface. We find that SbacHTS software can effectively detect and correct spatial background noise, increase signal to noise ratio and enhance statistical detection power in high-throughput RNAi screening experiments.

Availability

http://www.galaxy.qbrc.org/

SUBMITTER: Zhong R 

PROVIDER: S-EPMC3740628 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Publications

SbacHTS: spatial background noise correction for high-throughput RNAi screening.

Zhong Rui R   Kim Min Soo MS   White Michael A MA   Xie Yang Y   Xiao Guanghua G  

Bioinformatics (Oxford, England) 20130628 17


<h4>Motivation</h4>High-throughput cell-based phenotypic screening has become an increasingly important technology for discovering new drug targets and assigning gene functions. Such experiments use hundreds of 96-well or 384-well plates, to cover whole-genome RNAi collections and/or chemical compound files, and often collect measurements that are sensitive to spatial background noise whose patterns can vary across individual plates. Correcting these position effects can substantially improve me  ...[more]

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