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Analysis of probe level patterns in Affymetrix microarray data
BACKGROUND: Microarrays have been used extensively to analyze the expression profiles for thousands of genes in parallel. Most of the widely used methods for analyzing Affymetrix Genechip microarray data, including RMA, GCRMA and Model Based Expression Index (MBEI), summarize probe signal intensity...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1884176/ https://www.ncbi.nlm.nih.gov/pubmed/17480226 http://dx.doi.org/10.1186/1471-2105-8-146 |
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author | Cambon, Alexander C Khalyfa, Abdelnaby Cooper, Nigel GF Thompson, Caryn M |
author_facet | Cambon, Alexander C Khalyfa, Abdelnaby Cooper, Nigel GF Thompson, Caryn M |
author_sort | Cambon, Alexander C |
collection | PubMed |
description | BACKGROUND: Microarrays have been used extensively to analyze the expression profiles for thousands of genes in parallel. Most of the widely used methods for analyzing Affymetrix Genechip microarray data, including RMA, GCRMA and Model Based Expression Index (MBEI), summarize probe signal intensity data to generate a single measure of expression for each transcript on the array. In contrast, other methods are applied directly to probe intensities, negating the need for a summarization step. RESULTS: In this study, we used the Affymetrix rat genome Genechip to explore variability in probe response patterns within transcripts. We considered a number of possible sources of variability in probe sets including probe location within the transcript, middle base pair of the probe sequence, probe overlap, sequence homology and affinity. Although affinity, middle base pair and probe location effects may be seen at the gross array level, these factors only account for a small proportion of the variation observed at the gene level. A BLAST search and the presence of probe by treatment interactions for selected differentially expressed genes showed high sequence homology for many probes to non-target genes. CONCLUSION: We suggest that examination and modeling of probe level intensities can be used to guide researchers in refining their conclusions regarding differentially expressed genes. We discuss implications for probe sequence selection for confirmatory analysis using real time PCR. |
format | Text |
id | pubmed-1884176 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-18841762007-05-30 Analysis of probe level patterns in Affymetrix microarray data Cambon, Alexander C Khalyfa, Abdelnaby Cooper, Nigel GF Thompson, Caryn M BMC Bioinformatics Research Article BACKGROUND: Microarrays have been used extensively to analyze the expression profiles for thousands of genes in parallel. Most of the widely used methods for analyzing Affymetrix Genechip microarray data, including RMA, GCRMA and Model Based Expression Index (MBEI), summarize probe signal intensity data to generate a single measure of expression for each transcript on the array. In contrast, other methods are applied directly to probe intensities, negating the need for a summarization step. RESULTS: In this study, we used the Affymetrix rat genome Genechip to explore variability in probe response patterns within transcripts. We considered a number of possible sources of variability in probe sets including probe location within the transcript, middle base pair of the probe sequence, probe overlap, sequence homology and affinity. Although affinity, middle base pair and probe location effects may be seen at the gross array level, these factors only account for a small proportion of the variation observed at the gene level. A BLAST search and the presence of probe by treatment interactions for selected differentially expressed genes showed high sequence homology for many probes to non-target genes. CONCLUSION: We suggest that examination and modeling of probe level intensities can be used to guide researchers in refining their conclusions regarding differentially expressed genes. We discuss implications for probe sequence selection for confirmatory analysis using real time PCR. BioMed Central 2007-05-04 /pmc/articles/PMC1884176/ /pubmed/17480226 http://dx.doi.org/10.1186/1471-2105-8-146 Text en Copyright © 2007 Cambon 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 Cambon, Alexander C Khalyfa, Abdelnaby Cooper, Nigel GF Thompson, Caryn M Analysis of probe level patterns in Affymetrix microarray data |
title | Analysis of probe level patterns in Affymetrix microarray data |
title_full | Analysis of probe level patterns in Affymetrix microarray data |
title_fullStr | Analysis of probe level patterns in Affymetrix microarray data |
title_full_unstemmed | Analysis of probe level patterns in Affymetrix microarray data |
title_short | Analysis of probe level patterns in Affymetrix microarray data |
title_sort | analysis of probe level patterns in affymetrix microarray data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1884176/ https://www.ncbi.nlm.nih.gov/pubmed/17480226 http://dx.doi.org/10.1186/1471-2105-8-146 |
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