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How high is the level of technical noise in microarray data?
BACKGROUND: Microarray gene expression data are commonly perceived as being extremely noisy because of many imperfections inherent in the current technology. A recent study conducted by the MicroArray Quality Control (MAQC) Consortium and published in Nature Biotechnology provides a unique opportuni...
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1855048/ https://www.ncbi.nlm.nih.gov/pubmed/17428341 http://dx.doi.org/10.1186/1745-6150-2-9 |
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author | Klebanov, Lev Yakovlev, Andrei |
author_facet | Klebanov, Lev Yakovlev, Andrei |
author_sort | Klebanov, Lev |
collection | PubMed |
description | BACKGROUND: Microarray gene expression data are commonly perceived as being extremely noisy because of many imperfections inherent in the current technology. A recent study conducted by the MicroArray Quality Control (MAQC) Consortium and published in Nature Biotechnology provides a unique opportunity to probe into the true level of technical noise in such data. RESULTS: In the present report, the MAQC study is reanalyzed in order to quantitatively assess measurement errors inherent in high-density oligonucleotide array technology (Affymetrix platform). The level of noise is directly estimated from technical replicates of gene expression measurements in the absence of biological variability. For each probe set, the magnitude of random fluctuations across technical replicates is characterized by the standard deviation of the corresponding log-expression signal. The resultant standard deviations appear to be uniformly small and symmetrically distributed across probe sets. The observed noise level does not cause any tangible bias in estimated pair-wise correlation coefficients, the latter being particularly prone to its presence in microarray data. CONCLUSION: The reported analysis strongly suggests that, contrary to popular belief, the random fluctuations of gene expression signals caused by technical noise are quite low and the effect of such fluctuations on the results of statistical inference from Affymetrix GeneChip microarray data is negligibly small. REVIEWERS: The paper was reviewed by A. Mushegian, K. Jordan, and E. Koonin. |
format | Text |
id | pubmed-1855048 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18550482007-05-02 How high is the level of technical noise in microarray data? Klebanov, Lev Yakovlev, Andrei Biol Direct Research BACKGROUND: Microarray gene expression data are commonly perceived as being extremely noisy because of many imperfections inherent in the current technology. A recent study conducted by the MicroArray Quality Control (MAQC) Consortium and published in Nature Biotechnology provides a unique opportunity to probe into the true level of technical noise in such data. RESULTS: In the present report, the MAQC study is reanalyzed in order to quantitatively assess measurement errors inherent in high-density oligonucleotide array technology (Affymetrix platform). The level of noise is directly estimated from technical replicates of gene expression measurements in the absence of biological variability. For each probe set, the magnitude of random fluctuations across technical replicates is characterized by the standard deviation of the corresponding log-expression signal. The resultant standard deviations appear to be uniformly small and symmetrically distributed across probe sets. The observed noise level does not cause any tangible bias in estimated pair-wise correlation coefficients, the latter being particularly prone to its presence in microarray data. CONCLUSION: The reported analysis strongly suggests that, contrary to popular belief, the random fluctuations of gene expression signals caused by technical noise are quite low and the effect of such fluctuations on the results of statistical inference from Affymetrix GeneChip microarray data is negligibly small. REVIEWERS: The paper was reviewed by A. Mushegian, K. Jordan, and E. Koonin. BioMed Central 2007-04-11 /pmc/articles/PMC1855048/ /pubmed/17428341 http://dx.doi.org/10.1186/1745-6150-2-9 Text en Copyright © 2007 Klebanov and Yakovlev; 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 | Research Klebanov, Lev Yakovlev, Andrei How high is the level of technical noise in microarray data? |
title | How high is the level of technical noise in microarray data? |
title_full | How high is the level of technical noise in microarray data? |
title_fullStr | How high is the level of technical noise in microarray data? |
title_full_unstemmed | How high is the level of technical noise in microarray data? |
title_short | How high is the level of technical noise in microarray data? |
title_sort | how high is the level of technical noise in microarray data? |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1855048/ https://www.ncbi.nlm.nih.gov/pubmed/17428341 http://dx.doi.org/10.1186/1745-6150-2-9 |
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