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BioMed Central, BioData Mining, 1(9), 2016

DOI: 10.1186/s13040-016-0088-2

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Robust normalization protocols for multiplexed fluorescence bioimage analysis

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Postprint: archiving allowed
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Data provided by SHERPA/RoMEO

Abstract

The study of mapping and interaction of co-localized proteins at a sub-cellular level is important for understanding complex biological phenomena. One of the recent techniques to map co-localized proteins is to use the standard immuno-fluorescence microscopy in a cyclic manner (Nat Biotechnol 24:1270–8, 2006; Proc Natl Acad Sci 110:11982–7, 2013). Unfortunately, these techniques suffer from variability in intensity and positioning of signals from protein markers within a run and across different runs. Therefore, it is necessary to standardize protocols for preprocessing of the multiplexed bioimaging (MBI) data from multiple runs to a comparable scale before any further analysis can be performed on the data. In this paper, we compare various normalization protocols and propose on the basis of the obtained results, a robust normalization technique that produces consistent results on the MBI data collected from different runs using the Toponome Imaging System (TIS). Normalization results produced by the proposed method on a sample TIS data set for colorectal cancer patients were ranked favorably by two pathologists and two biologists. We show that the proposed method produces higher between class Kullback-Leibler (KL) divergence and lower within class KL divergence on a distribution of cell phenotypes from colorectal cancer and histologically normal samples. ; UK BBSRC and the Qatar National Research Fund (QNRF) for partially supporting this study through project grants BB/K018868/1 and NPRP 5-1345-1-228, respectively.