July 24, 2019
Skip to article ;Using an automated liquid-handling robot such as the HP D300e Digital Dispenser, it is possible to dispense compounds directly into microtiter plates in an arbitrary pattern, randomizing the locations of control and technical replicates and converting systematic error into ;Using an automated liquid-handling robot such as the HP D300e Digital Dispenser, it is possible to dispense compounds directly into microtiter plates in an arbitrary pattern, randomizing the locations of control and technical replicates and converting systematic error into
Evidence that some high-impact biomedical results cannot be repeated has stimulated interest in practices that generate findable, accessible, interoperable, and reusable (FAIR) data. Multiple papers have identified specific examples of irreproducibility, but practical ways to make data more reproducible have not been widely studied. Here, five research centers in the NIH LINCS Program Consortium investigate the reproducibility of a prototypical perturbational assay: quantifying the responsiveness of cultured cells to anti-cancer drugs. Such assays are important for drug development, studying cellular networks, and patient stratification. While many experimental and computational factors impact intra- and inter-center reproducibility, the factors most difficult to identify and control are those with a strong dependency on biological context. These factors often vary in magnitude with the drug being analyzed and with growth conditions. We provide ways to identify such context-sensitive factors, thereby improving both the theory and practice of reproducible cell-based assays. Copyright Š 2019 The Authors. Published by Elsevier Inc. All rights reserved.
Niepel, M; Hafner, M; Mills, CE; Subramanian, K; Williams, EH; Chung, M; Gaudio, B; Barrette, AM; Stern, AD; Hu, B; Korkola, JE; , ; Gray, JW; Birtwistle, MR; Heiser, LM; Sorger, PK;
Journal: Cell Syst Pages: 35-48.e5