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Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data

BACKGROUND: For 2-dye microarray platforms, some missing values may arise from an un-measurably low RNA expression in one channel only. Information of such "one-channel depletion" is so far not included in algorithms for imputation of missing values. RESULTS: Calculating the mean deviation...

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Detalles Bibliográficos
Autores principales: Ritz, Cecilia, Edén, Patrik
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2267710/
https://www.ncbi.nlm.nih.gov/pubmed/18205949
http://dx.doi.org/10.1186/1471-2164-9-25
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author Ritz, Cecilia
Edén, Patrik
author_facet Ritz, Cecilia
Edén, Patrik
author_sort Ritz, Cecilia
collection PubMed
description BACKGROUND: For 2-dye microarray platforms, some missing values may arise from an un-measurably low RNA expression in one channel only. Information of such "one-channel depletion" is so far not included in algorithms for imputation of missing values. RESULTS: Calculating the mean deviation between imputed values and duplicate controls in five datasets, we show that KNN-based imputation gives a systematic bias of the imputed expression values of one-channel depleted spots. Evaluating the correction of this bias by cross-validation showed that the mean square deviation between imputed values and duplicates were reduced up to 51%, depending on dataset. CONCLUSION: By including more information in the imputation step, we more accurately estimate missing expression values.
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spelling pubmed-22677102008-03-17 Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data Ritz, Cecilia Edén, Patrik BMC Genomics Methodology Article BACKGROUND: For 2-dye microarray platforms, some missing values may arise from an un-measurably low RNA expression in one channel only. Information of such "one-channel depletion" is so far not included in algorithms for imputation of missing values. RESULTS: Calculating the mean deviation between imputed values and duplicate controls in five datasets, we show that KNN-based imputation gives a systematic bias of the imputed expression values of one-channel depleted spots. Evaluating the correction of this bias by cross-validation showed that the mean square deviation between imputed values and duplicates were reduced up to 51%, depending on dataset. CONCLUSION: By including more information in the imputation step, we more accurately estimate missing expression values. BioMed Central 2008-01-19 /pmc/articles/PMC2267710/ /pubmed/18205949 http://dx.doi.org/10.1186/1471-2164-9-25 Text en Copyright © 2008 Ritz and Edén; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Ritz, Cecilia
Edén, Patrik
Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
title Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
title_full Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
title_fullStr Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
title_full_unstemmed Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
title_short Accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
title_sort accounting for one-channel depletion improves missing value imputation in 2-dye microarray data
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2267710/
https://www.ncbi.nlm.nih.gov/pubmed/18205949
http://dx.doi.org/10.1186/1471-2164-9-25
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