Statistical and visual differentiation of subcellular imaging
Open Access
- 22 March 2009
- journal article
- Published by Springer Science and Business Media LLC in BMC Bioinformatics
- Vol. 10 (1), 94
- https://doi.org/10.1186/1471-2105-10-94
Abstract
Automated microscopy technologies have led to a rapid growth in imaging data on a scale comparable to that of the genomic revolution. High throughput screens are now being performed to determine the localisation of all of proteins in a proteome. Closer to the bench, large image sets of proteins in treated and untreated cells are being captured on a daily basis to determine function and interactions. Hence there is a need for new methodologies and protocols to test for difference in subcellular imaging both to remove bias and enable throughput. Here we introduce a novel method of statistical testing, and supporting software, to give a rigorous test for difference in imaging. We also outline the key questions and steps in establishing an analysis pipeline.Keywords
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