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A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data
BACKGROUND: Affymetrix GeneChip typically contains multiple probe sets per gene, defined as sibling probe sets in this study. These probe sets may or may not behave similar across treatments. The most appropriate way of consolidating sibling probe sets suitable for analysis is an open problem. We pr...
Autores principales: | , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2008
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2397416/ https://www.ncbi.nlm.nih.gov/pubmed/18435860 http://dx.doi.org/10.1186/1471-2164-9-188 |
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author | Li, Hua Zhu, Dongxiao Cook, Malcolm |
author_facet | Li, Hua Zhu, Dongxiao Cook, Malcolm |
author_sort | Li, Hua |
collection | PubMed |
description | BACKGROUND: Affymetrix GeneChip typically contains multiple probe sets per gene, defined as sibling probe sets in this study. These probe sets may or may not behave similar across treatments. The most appropriate way of consolidating sibling probe sets suitable for analysis is an open problem. We propose the Analysis of Variance (ANOVA) framework to decide which sibling probe sets can be consolidated. RESULTS: The ANOVA model allows us to separate the sibling probe sets into two types: those behave similarly across treatments and those behave differently across treatments. We found that consolidation of sibling probe sets of the former type results in large increase in the number of differentially expressed genes under various statistical criteria. The approach to selecting sibling probe sets suitable for consolidating is implemented in R language and freely available from . CONCLUSION: Our ANOVA analysis of sibling probe sets provides a statistical framework for selecting sibling probe sets for consolidation. Consolidating sibling probe sets by pooling data from each greatly improves the estimates of a gene expression level and results in identification of more biologically relevant genes. Sibling probe sets that do not qualify for consolidation may represent annotation errors or other artifacts, or may correspond to differentially processed transcripts of the same gene that require further analysis. |
format | Text |
id | pubmed-2397416 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-23974162008-05-29 A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data Li, Hua Zhu, Dongxiao Cook, Malcolm BMC Genomics Research Article BACKGROUND: Affymetrix GeneChip typically contains multiple probe sets per gene, defined as sibling probe sets in this study. These probe sets may or may not behave similar across treatments. The most appropriate way of consolidating sibling probe sets suitable for analysis is an open problem. We propose the Analysis of Variance (ANOVA) framework to decide which sibling probe sets can be consolidated. RESULTS: The ANOVA model allows us to separate the sibling probe sets into two types: those behave similarly across treatments and those behave differently across treatments. We found that consolidation of sibling probe sets of the former type results in large increase in the number of differentially expressed genes under various statistical criteria. The approach to selecting sibling probe sets suitable for consolidating is implemented in R language and freely available from . CONCLUSION: Our ANOVA analysis of sibling probe sets provides a statistical framework for selecting sibling probe sets for consolidation. Consolidating sibling probe sets by pooling data from each greatly improves the estimates of a gene expression level and results in identification of more biologically relevant genes. Sibling probe sets that do not qualify for consolidation may represent annotation errors or other artifacts, or may correspond to differentially processed transcripts of the same gene that require further analysis. BioMed Central 2008-04-24 /pmc/articles/PMC2397416/ /pubmed/18435860 http://dx.doi.org/10.1186/1471-2164-9-188 Text en Copyright © 2008 Li et al; 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 Article Li, Hua Zhu, Dongxiao Cook, Malcolm A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data |
title | A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data |
title_full | A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data |
title_fullStr | A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data |
title_full_unstemmed | A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data |
title_short | A statistical framework for consolidating "sibling" probe sets for Affymetrix GeneChip data |
title_sort | statistical framework for consolidating "sibling" probe sets for affymetrix genechip data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2397416/ https://www.ncbi.nlm.nih.gov/pubmed/18435860 http://dx.doi.org/10.1186/1471-2164-9-188 |
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