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Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor
The presence of different transcripts of a gene across samples can be analysed by whole-transcriptome microarrays. Reproducing results from published microarray data represents a challenge owing to the vast amounts of data and the large variety of preprocessing and filtering steps used before the ac...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103539/ https://www.ncbi.nlm.nih.gov/pubmed/23603090 http://dx.doi.org/10.1093/bib/bbt011 |
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author | Rodrigo-Domingo, Maria Waagepetersen, Rasmus Bødker, Julie Støve Falgreen, Steffen Kjeldsen, Malene Krag Johnsen, Hans Erik Dybkær, Karen Bøgsted, Martin |
author_facet | Rodrigo-Domingo, Maria Waagepetersen, Rasmus Bødker, Julie Støve Falgreen, Steffen Kjeldsen, Malene Krag Johnsen, Hans Erik Dybkær, Karen Bøgsted, Martin |
author_sort | Rodrigo-Domingo, Maria |
collection | PubMed |
description | The presence of different transcripts of a gene across samples can be analysed by whole-transcriptome microarrays. Reproducing results from published microarray data represents a challenge owing to the vast amounts of data and the large variety of preprocessing and filtering steps used before the actual analysis is carried out. To guarantee a firm basis for methodological development where results with new methods are compared with previous results, it is crucial to ensure that all analyses are completely reproducible for other researchers. We here give a detailed workflow on how to perform reproducible analysis of the GeneChip®Human Exon 1.0 ST Array at probe and probeset level solely in R/Bioconductor, choosing packages based on their simplicity of use. To exemplify the use of the proposed workflow, we analyse differential splicing and differential gene expression in a publicly available dataset using various statistical methods. We believe this study will provide other researchers with an easy way of accessing gene expression data at different annotation levels and with the sufficient details needed for developing their own tools for reproducible analysis of the GeneChip®Human Exon 1.0 ST Array. |
format | Online Article Text |
id | pubmed-4103539 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-41035392014-07-18 Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor Rodrigo-Domingo, Maria Waagepetersen, Rasmus Bødker, Julie Støve Falgreen, Steffen Kjeldsen, Malene Krag Johnsen, Hans Erik Dybkær, Karen Bøgsted, Martin Brief Bioinform Papers The presence of different transcripts of a gene across samples can be analysed by whole-transcriptome microarrays. Reproducing results from published microarray data represents a challenge owing to the vast amounts of data and the large variety of preprocessing and filtering steps used before the actual analysis is carried out. To guarantee a firm basis for methodological development where results with new methods are compared with previous results, it is crucial to ensure that all analyses are completely reproducible for other researchers. We here give a detailed workflow on how to perform reproducible analysis of the GeneChip®Human Exon 1.0 ST Array at probe and probeset level solely in R/Bioconductor, choosing packages based on their simplicity of use. To exemplify the use of the proposed workflow, we analyse differential splicing and differential gene expression in a publicly available dataset using various statistical methods. We believe this study will provide other researchers with an easy way of accessing gene expression data at different annotation levels and with the sufficient details needed for developing their own tools for reproducible analysis of the GeneChip®Human Exon 1.0 ST Array. Oxford University Press 2014-07 2013-04-19 /pmc/articles/PMC4103539/ /pubmed/23603090 http://dx.doi.org/10.1093/bib/bbt011 Text en © The Author 2013. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Papers Rodrigo-Domingo, Maria Waagepetersen, Rasmus Bødker, Julie Støve Falgreen, Steffen Kjeldsen, Malene Krag Johnsen, Hans Erik Dybkær, Karen Bøgsted, Martin Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor |
title | Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor |
title_full | Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor |
title_fullStr | Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor |
title_full_unstemmed | Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor |
title_short | Reproducible probe-level analysis of the Affymetrix Exon 1.0 ST array with R/Bioconductor |
title_sort | reproducible probe-level analysis of the affymetrix exon 1.0 st array with r/bioconductor |
topic | Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103539/ https://www.ncbi.nlm.nih.gov/pubmed/23603090 http://dx.doi.org/10.1093/bib/bbt011 |
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