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Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool
Microarray technology is currently one of the most widely-used technologies in biology. Many studies focus on inferring the function of an unknown gene from its co-expressed genes. Here, we are able to show that there are two types of positional artifacts in microarray data introducing spurious corr...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1802630/ https://www.ncbi.nlm.nih.gov/pubmed/17158151 http://dx.doi.org/10.1093/nar/gkl871 |
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author | Yu, Haiyuan Nguyen, Katherine Royce, Tom Qian, Jiang Nelson, Kenneth Snyder, Michael Gerstein, Mark |
author_facet | Yu, Haiyuan Nguyen, Katherine Royce, Tom Qian, Jiang Nelson, Kenneth Snyder, Michael Gerstein, Mark |
author_sort | Yu, Haiyuan |
collection | PubMed |
description | Microarray technology is currently one of the most widely-used technologies in biology. Many studies focus on inferring the function of an unknown gene from its co-expressed genes. Here, we are able to show that there are two types of positional artifacts in microarray data introducing spurious correlations between genes. First, we find that genes that are close on the microarray chips tend to have higher correlations between their expression profiles. We call this the ‘chip artifact’. Our calculations suggest that the carry-over during the printing process is one of the major sources of this type of artifact, which is later confirmed by our experiments. Based on our experiments, the measured intensity of a microarray spot contains 0.1% (for fully-hybridized spots) to 93% (for un-hybridized ones) of noise resulting from this artifact. Secondly, we, for the first time, show that genes that are close on the microtiter plates in microarray experiments also tend to have higher correlations. We call this the ‘plate artifact’. Both types of artifacts exist with different severity in all cDNA microarray experiments that we analyzed. Therefore, we develop an automated web tool—COP (COrrelations by Positional artifacts) to detect these artifacts in microarray experiments. COP has been integrated with the microarray data normalization tool, ExpressYourself, which is available at . Together, the two can eliminate most of the common noises in microarray data. |
format | Text |
id | pubmed-1802630 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-18026302007-03-01 Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool Yu, Haiyuan Nguyen, Katherine Royce, Tom Qian, Jiang Nelson, Kenneth Snyder, Michael Gerstein, Mark Nucleic Acids Res Methods Online Microarray technology is currently one of the most widely-used technologies in biology. Many studies focus on inferring the function of an unknown gene from its co-expressed genes. Here, we are able to show that there are two types of positional artifacts in microarray data introducing spurious correlations between genes. First, we find that genes that are close on the microarray chips tend to have higher correlations between their expression profiles. We call this the ‘chip artifact’. Our calculations suggest that the carry-over during the printing process is one of the major sources of this type of artifact, which is later confirmed by our experiments. Based on our experiments, the measured intensity of a microarray spot contains 0.1% (for fully-hybridized spots) to 93% (for un-hybridized ones) of noise resulting from this artifact. Secondly, we, for the first time, show that genes that are close on the microtiter plates in microarray experiments also tend to have higher correlations. We call this the ‘plate artifact’. Both types of artifacts exist with different severity in all cDNA microarray experiments that we analyzed. Therefore, we develop an automated web tool—COP (COrrelations by Positional artifacts) to detect these artifacts in microarray experiments. COP has been integrated with the microarray data normalization tool, ExpressYourself, which is available at . Together, the two can eliminate most of the common noises in microarray data. Oxford University Press 2007-01 2006-12-07 /pmc/articles/PMC1802630/ /pubmed/17158151 http://dx.doi.org/10.1093/nar/gkl871 Text en © 2006 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Yu, Haiyuan Nguyen, Katherine Royce, Tom Qian, Jiang Nelson, Kenneth Snyder, Michael Gerstein, Mark Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool |
title | Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool |
title_full | Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool |
title_fullStr | Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool |
title_full_unstemmed | Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool |
title_short | Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool |
title_sort | positional artifacts in microarrays: experimental verification and construction of cop, an automated detection tool |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1802630/ https://www.ncbi.nlm.nih.gov/pubmed/17158151 http://dx.doi.org/10.1093/nar/gkl871 |
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