학술논문

Detection and removal of spatial bias in multiwell assays.
Document Type
Article
Source
Bioinformatics. 7/1/2016, Vol. 32 Issue 13, p1959-1965. 7p.
Subject
*MICROFLUIDIC analytical techniques
*GENE expression profiling
*MICROPLATES
*HIGH throughput screening (Drug development)
*OLIGONUCLEOTIDE synthesis
Language
ISSN
1367-4803
Abstract
Motivation: Multiplex readout assays are now increasingly being performed using microfluidic automation in multiwell format. For instance, the Library of Integrated Network-based Cellular Signatures (LINCS) has produced gene expression measurements for tens of thousands of distinct cell perturbations using a 384-well plate format. This dataset is by far the largest 384-well gene expression measurement assay ever performed. We investigated the gene expression profiles of a million samples from the LINCS dataset and found that the vast majority (96%) of the tested plates were affected by a significant 2D spatial bias. Results: Using a novel algorithm combining spatial autocorrelation detection and principal component analysis, we could remove most of the spatial bias from the LINCS dataset and show in parallel a dramatic improvement of similarity between biological replicates assayed in different plates. The proposed methodology is fully general and can be applied to any highly multiplexed assay performed in multiwell format. [ABSTRACT FROM AUTHOR]