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Robust normalization protocols for multiplexed fluorescence bioimage analysis
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,...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4779207/ https://www.ncbi.nlm.nih.gov/pubmed/26949415 http://dx.doi.org/10.1186/s13040-016-0088-2 |
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author | Ahmed Raza, Shan E Langenkämper, Daniel Sirinukunwattana, Korsuk Epstein, David Nattkemper, Tim W. Rajpoot, Nasir M. |
author_facet | Ahmed Raza, Shan E Langenkämper, Daniel Sirinukunwattana, Korsuk Epstein, David Nattkemper, Tim W. Rajpoot, Nasir M. |
author_sort | Ahmed Raza, Shan E |
collection | PubMed |
description | 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13040-016-0088-2) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4779207 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-47792072016-03-06 Robust normalization protocols for multiplexed fluorescence bioimage analysis Ahmed Raza, Shan E Langenkämper, Daniel Sirinukunwattana, Korsuk Epstein, David Nattkemper, Tim W. Rajpoot, Nasir M. BioData Min Research 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13040-016-0088-2) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-05 /pmc/articles/PMC4779207/ /pubmed/26949415 http://dx.doi.org/10.1186/s13040-016-0088-2 Text en © Raza et al. 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Ahmed Raza, Shan E Langenkämper, Daniel Sirinukunwattana, Korsuk Epstein, David Nattkemper, Tim W. Rajpoot, Nasir M. Robust normalization protocols for multiplexed fluorescence bioimage analysis |
title | Robust normalization protocols for multiplexed fluorescence bioimage analysis |
title_full | Robust normalization protocols for multiplexed fluorescence bioimage analysis |
title_fullStr | Robust normalization protocols for multiplexed fluorescence bioimage analysis |
title_full_unstemmed | Robust normalization protocols for multiplexed fluorescence bioimage analysis |
title_short | Robust normalization protocols for multiplexed fluorescence bioimage analysis |
title_sort | robust normalization protocols for multiplexed fluorescence bioimage analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4779207/ https://www.ncbi.nlm.nih.gov/pubmed/26949415 http://dx.doi.org/10.1186/s13040-016-0088-2 |
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