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Escherichia coli O157:H7 transcriptome datasets for comparison of RNA-seq and microarray platforms
Whole transcriptome analysis to investigate differential gene expression and regulatory adaption can be carried out on two different technological platforms: by probe hybridisation to microarrays or by RNAseq for deep sequencing. Since there are difference in terms of their genome coverage, sensitiv...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6297237/ https://www.ncbi.nlm.nih.gov/pubmed/30581915 http://dx.doi.org/10.1016/j.dib.2018.11.136 |
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author | Grabowiecka, Ewa Martin, David Crozier, Louise Holden, Nicola |
author_facet | Grabowiecka, Ewa Martin, David Crozier, Louise Holden, Nicola |
author_sort | Grabowiecka, Ewa |
collection | PubMed |
description | Whole transcriptome analysis to investigate differential gene expression and regulatory adaption can be carried out on two different technological platforms: by probe hybridisation to microarrays or by RNAseq for deep sequencing. Since there are difference in terms of their genome coverage, sensitivity and cost, there is a requirement for robust comparisons to determine the platform of choice. Here, we present datasets for the whole transcriptional response verocytoxigenic Escherichia coli (VTEC) obtained from RNA-seq and microarray platforms in response to spinach, together with a comparison between the datasets (available at Array Express: E-MTAB-3249, E-MTAB-4120, E-MTAB-7441). |
format | Online Article Text |
id | pubmed-6297237 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-62972372018-12-21 Escherichia coli O157:H7 transcriptome datasets for comparison of RNA-seq and microarray platforms Grabowiecka, Ewa Martin, David Crozier, Louise Holden, Nicola Data Brief Immunology and Microbiology Whole transcriptome analysis to investigate differential gene expression and regulatory adaption can be carried out on two different technological platforms: by probe hybridisation to microarrays or by RNAseq for deep sequencing. Since there are difference in terms of their genome coverage, sensitivity and cost, there is a requirement for robust comparisons to determine the platform of choice. Here, we present datasets for the whole transcriptional response verocytoxigenic Escherichia coli (VTEC) obtained from RNA-seq and microarray platforms in response to spinach, together with a comparison between the datasets (available at Array Express: E-MTAB-3249, E-MTAB-4120, E-MTAB-7441). Elsevier 2018-11-30 /pmc/articles/PMC6297237/ /pubmed/30581915 http://dx.doi.org/10.1016/j.dib.2018.11.136 Text en Crown Copyright © 2018 Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Immunology and Microbiology Grabowiecka, Ewa Martin, David Crozier, Louise Holden, Nicola Escherichia coli O157:H7 transcriptome datasets for comparison of RNA-seq and microarray platforms |
title | Escherichia coli O157:H7 transcriptome datasets for comparison of RNA-seq and microarray platforms |
title_full | Escherichia coli O157:H7 transcriptome datasets for comparison of RNA-seq and microarray platforms |
title_fullStr | Escherichia coli O157:H7 transcriptome datasets for comparison of RNA-seq and microarray platforms |
title_full_unstemmed | Escherichia coli O157:H7 transcriptome datasets for comparison of RNA-seq and microarray platforms |
title_short | Escherichia coli O157:H7 transcriptome datasets for comparison of RNA-seq and microarray platforms |
title_sort | escherichia coli o157:h7 transcriptome datasets for comparison of rna-seq and microarray platforms |
topic | Immunology and Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6297237/ https://www.ncbi.nlm.nih.gov/pubmed/30581915 http://dx.doi.org/10.1016/j.dib.2018.11.136 |
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