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Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset
Microarray gene expression data has been used in genome-wide association studies to allow researchers to study gene regulation as well as other complex phenotypes including disease risks and drug response. To reach scientifically sound conclusions from these studies, however, it is necessary to get...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2826392/ https://www.ncbi.nlm.nih.gov/pubmed/20186275 http://dx.doi.org/10.1371/journal.pone.0009366 |
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author | Gamazon, Eric R. Zhang, Wei Dolan, M. Eileen Cox, Nancy J. |
author_facet | Gamazon, Eric R. Zhang, Wei Dolan, M. Eileen Cox, Nancy J. |
author_sort | Gamazon, Eric R. |
collection | PubMed |
description | Microarray gene expression data has been used in genome-wide association studies to allow researchers to study gene regulation as well as other complex phenotypes including disease risks and drug response. To reach scientifically sound conclusions from these studies, however, it is necessary to get reliable summarization of gene expression intensities. Among various factors that could affect expression profiling using a microarray platform, single nucleotide polymorphisms (SNPs) in target mRNA may lead to reduced signal intensity measurements and result in spurious results. The recently released 1000 Genomes Project dataset provides an opportunity to evaluate the distribution of both known and novel SNPs in the International HapMap Project lymphoblastoid cell lines (LCLs). We mapped the 1000 Genomes Project genotypic data to the Affymetrix GeneChip Human Exon 1.0ST array (exon array), which had been used in our previous studies and for which gene expression data had been made publicly available. We also evaluated the potential impact of these SNPs on the differentially spliced probesets we had identified previously. Though the 1000 Genomes Project data allowed a comprehensive survey of the SNPs in this particular array, the same approach can certainly be applied to other microarray platforms. Furthermore, we present a detailed catalogue of SNP-containing probesets (exon-level) and transcript clusters (gene-level), which can be considered in evaluating findings using the exon array as well as benefit the design of follow-up experiments and data re-analysis. |
format | Text |
id | pubmed-2826392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28263922010-02-26 Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset Gamazon, Eric R. Zhang, Wei Dolan, M. Eileen Cox, Nancy J. PLoS One Research Article Microarray gene expression data has been used in genome-wide association studies to allow researchers to study gene regulation as well as other complex phenotypes including disease risks and drug response. To reach scientifically sound conclusions from these studies, however, it is necessary to get reliable summarization of gene expression intensities. Among various factors that could affect expression profiling using a microarray platform, single nucleotide polymorphisms (SNPs) in target mRNA may lead to reduced signal intensity measurements and result in spurious results. The recently released 1000 Genomes Project dataset provides an opportunity to evaluate the distribution of both known and novel SNPs in the International HapMap Project lymphoblastoid cell lines (LCLs). We mapped the 1000 Genomes Project genotypic data to the Affymetrix GeneChip Human Exon 1.0ST array (exon array), which had been used in our previous studies and for which gene expression data had been made publicly available. We also evaluated the potential impact of these SNPs on the differentially spliced probesets we had identified previously. Though the 1000 Genomes Project data allowed a comprehensive survey of the SNPs in this particular array, the same approach can certainly be applied to other microarray platforms. Furthermore, we present a detailed catalogue of SNP-containing probesets (exon-level) and transcript clusters (gene-level), which can be considered in evaluating findings using the exon array as well as benefit the design of follow-up experiments and data re-analysis. Public Library of Science 2010-02-23 /pmc/articles/PMC2826392/ /pubmed/20186275 http://dx.doi.org/10.1371/journal.pone.0009366 Text en Gamazon et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Gamazon, Eric R. Zhang, Wei Dolan, M. Eileen Cox, Nancy J. Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset |
title | Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset |
title_full | Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset |
title_fullStr | Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset |
title_full_unstemmed | Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset |
title_short | Comprehensive Survey of SNPs in the Affymetrix Exon Array Using the 1000 Genomes Dataset |
title_sort | comprehensive survey of snps in the affymetrix exon array using the 1000 genomes dataset |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2826392/ https://www.ncbi.nlm.nih.gov/pubmed/20186275 http://dx.doi.org/10.1371/journal.pone.0009366 |
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