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Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome

Motivation: We investigate and quantify the generalizability of the white blood cell (WBC) transcriptome to the general, multiorgan transcriptome. We use data from the NCBI's Gene Expression Omnibus (GEO) public repository to define two datasets for comparison, WBC and OO (Other Organ) sets. Re...

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Detalles Bibliográficos
Autores principales: Kohane, Isaac S., Valtchinov, Vladimir I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3288749/
https://www.ncbi.nlm.nih.gov/pubmed/22219206
http://dx.doi.org/10.1093/bioinformatics/btr713
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author Kohane, Isaac S.
Valtchinov, Vladimir I.
author_facet Kohane, Isaac S.
Valtchinov, Vladimir I.
author_sort Kohane, Isaac S.
collection PubMed
description Motivation: We investigate and quantify the generalizability of the white blood cell (WBC) transcriptome to the general, multiorgan transcriptome. We use data from the NCBI's Gene Expression Omnibus (GEO) public repository to define two datasets for comparison, WBC and OO (Other Organ) sets. Results: Comprehensive pair-wise correlation and expression level profiles are calculated for both datasets (with sizes of 81 and 1463, respectively). We have used mapping and ranking across the Gene Ontology (GO) categories to quantify similarity between the two sets. GO mappings of the most correlated and highly expressed genes from the two datasets tightly match, with the notable exceptions of components of the ribosome, cell adhesion and immune response. That is, 10 877 or 48.8% of all measured genes do not change >10% of rank range between WBC and OO; only 878 (3.9%) change rank >50%. Two trans-tissue gene lists are defined, the most changing and the least changing genes in expression rank. We also provide a general, quantitative measure of the probability of expression rank and correlation profile in the OO system given the expression rank and correlation profile in the WBC dataset. Contact: vvaltchinov@partners.org Supplementary information: Supplementary data are available at Bioinformatics online.
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spelling pubmed-32887492012-10-05 Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome Kohane, Isaac S. Valtchinov, Vladimir I. Bioinformatics Original Papers Motivation: We investigate and quantify the generalizability of the white blood cell (WBC) transcriptome to the general, multiorgan transcriptome. We use data from the NCBI's Gene Expression Omnibus (GEO) public repository to define two datasets for comparison, WBC and OO (Other Organ) sets. Results: Comprehensive pair-wise correlation and expression level profiles are calculated for both datasets (with sizes of 81 and 1463, respectively). We have used mapping and ranking across the Gene Ontology (GO) categories to quantify similarity between the two sets. GO mappings of the most correlated and highly expressed genes from the two datasets tightly match, with the notable exceptions of components of the ribosome, cell adhesion and immune response. That is, 10 877 or 48.8% of all measured genes do not change >10% of rank range between WBC and OO; only 878 (3.9%) change rank >50%. Two trans-tissue gene lists are defined, the most changing and the least changing genes in expression rank. We also provide a general, quantitative measure of the probability of expression rank and correlation profile in the OO system given the expression rank and correlation profile in the WBC dataset. Contact: vvaltchinov@partners.org Supplementary information: Supplementary data are available at Bioinformatics online. Oxford University Press 2012-02-15 2012-01-04 /pmc/articles/PMC3288749/ /pubmed/22219206 http://dx.doi.org/10.1093/bioinformatics/btr713 Text en © The Author(s) 2012. 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 unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Papers
Kohane, Isaac S.
Valtchinov, Vladimir I.
Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome
title Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome
title_full Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome
title_fullStr Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome
title_full_unstemmed Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome
title_short Quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome
title_sort quantifying the white blood cell transcriptome as an accessible window to the multiorgan transcriptome
topic Original Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3288749/
https://www.ncbi.nlm.nih.gov/pubmed/22219206
http://dx.doi.org/10.1093/bioinformatics/btr713
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