Analysis of image-based phenotypic parameters for high throughput gene perturbation assays |
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| Institution: | 1. Center for Advanced Bioinformatics & Systems Medicine, Sookmyung Women’s University, Seoul 140-742, Republic of Korea;2. Discovery Biology Group, Institute Pasteur Korea, Seongnam-si, Gyeonggi-do 463-400, Republic of Korea;3. Imaging Processing Platform, Institute Pasteur Korea, Seongnam-si, Gyeonggi-do 463-400, Republic of Korea;4. Department of Biological Sciences, Sookmyung Women’s University, Seoul 140-742, Republic of Korea;1. Department of Chemistry, University of Louisiana at Lafayette, Lafayette, LA 70504, United States;2. Department of Mechanical Engineering, Mississippi State University, Mississippi State, MS 39762, United States;3. The Center for Advanced Computer Studies, University of Louisiana at Lafayette, Lafayette, LA 70504, United States;1. Computer & Telecommunication Engineering Division, Yonsei University, Wonju, Gangwon-Do 26493, Republic of Korea;2. Department of Computer Science, Sookmyung Women׳s University, Seoul 04310, Republic of Korea;1. Grupo de Materiales y Sistemas Catalíticos, Instituto de Física del Sur, Departamento de Física, Universidad Nacional del Sur, Av. Alem 1253, 8000 Bahía Blanca, Argentina;2. Instituto de Química del Sur, Departamento de Química, Universidad Nacional del Sur, Av. Alem 1253, 8000 Bahía Blanca, Argentina;1. College of Electronics, Communication and Physics, Shandong University of Science and Technology, Qingdao, 266590 Shandong, People’s Republic of China;2. College of Electrical Engineering and Automation, Shandong University of Science and Technology, Qingdao, 266590 Shandong, People’s Republic of China;1. Far Eastern Federal University, 8 Sukhanova St., Vladivostok, 690950, Russia;2. Vladivostok Branch of Russian Customs Academy, 16v Strelkovaya St., Vladivostok, 690034, Russia |
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| Abstract: | Although image-based phenotypic assays are considered a powerful tool for siRNA library screening, the reproducibility and biological implications of various image-based assays are not well-characterized in a systematic manner. Here, we compared the resolution of high throughput assays of image-based cell count and typical cell viability measures for cancer samples. It was found that the optimal plating density of cells was important to obtain maximal resolution in both types of assays. In general, cell counting provided better resolution than the cell viability measure in diverse batches of siRNAs. In addition to cell count, diverse image-based measures were simultaneously collected from a single screening and showed good reproducibility in repetitions. They were classified into a few functional categories according to biological process, based on the differential patterns of hit (i.e., siRNAs) prioritization from the same screening data. The presented systematic analyses of image-based parameters provide new insight to a multitude of applications and better biological interpretation of high content cell-based assays. |
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| Keywords: | siRNA screening Gene perturbation Image-based assay Phenotypic parameter |
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