Title: Exploratory analysis of cell-based screening data for phenotype identification in drug-siRNA study
Authors: William-Chandra Tjhi, Kee Khoon Lee, Terence Hung, Ivor Wai-Hung Tsang, Yew Soon Ong, Frederic Bard, Victor Racine
Addresses: Department of Computing Science, Institute of High Performance Computing, 1 Fusionopolis Way, #16-16 Connexis 138632, Singapore. ' Department of Computing Science, Institute of High Performance Computing, 1 Fusionopolis Way, #16-16 Connexis 138632, Singapore. ' Department of Computing Science, Institute of High Performance Computing, 1 Fusionopolis Way, #16-16 Connexis 138632, Singapore. ' School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue 639798, Singapore. ' School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue 639798, Singapore. ' Cell Structure and Function Research Group, Institute of Molecular and Cell Biology, 61 Biopolis Drive Proteos 138673, Singapore. ' Department of Imaging Shared Facility and Molecular Controls of Morphogenesis and Tumour Progression, Institute of Molecular and Cell Biology, 61 Biopolis Drive Proteos 138673, Singapore
Abstract: Most phenotype-identification methods in cell-based screening assume prior knowledge about expected phenotypes or involve intricate parameter-setting. They are useful for analysis targeting known phenotype properties; but need exists to explore, with minimum presumptions, the potentially-interesting phenotypes derivable from data. We present a method for this exploration, using clustering to eliminate phenotype-labelling requirement and GUI visualisation to facilitate parameter-setting. The steps are: outlier-removal, cell clustering and interactive visualisation for phenotypes refinement. For drug-siRNA study, we introduce an auto-merging procedure to reduce phenotype redundancy. We validated the method on two Golgi apparatus screens and showcase its contribution for better understanding of screening-images.
Keywords: cell-based screening; exploratory data analysis; phenotype clustering; visualisation; high content screening; Golgi apparatus; drug discovery; siRNA; phenotype identification; phenotypes; outlier removal; cell clustering.
DOI: 10.1504/IJCBDD.2011.041011
International Journal of Computational Biology and Drug Design, 2011 Vol.4 No.2, pp.194 - 215
Published online: 24 Jan 2015 *
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