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The tspair package for finding top scoring pair classifiers in R

Summary: Top scoring pairs (TSPs) are pairs of genes whose relative rankings can be used to accurately classify individuals into one of two classes. TSPs have two main advantages over many standard classifiers used in gene expression studies: (i) a TSP is based on only two genes, which leads to easi...

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Detalles Bibliográficos
Autor principal: Leek, Jeffrey T.
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672632/
https://www.ncbi.nlm.nih.gov/pubmed/19276151
http://dx.doi.org/10.1093/bioinformatics/btp126
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author Leek, Jeffrey T.
author_facet Leek, Jeffrey T.
author_sort Leek, Jeffrey T.
collection PubMed
description Summary: Top scoring pairs (TSPs) are pairs of genes whose relative rankings can be used to accurately classify individuals into one of two classes. TSPs have two main advantages over many standard classifiers used in gene expression studies: (i) a TSP is based on only two genes, which leads to easily interpretable and inexpensive diagnostic tests and (ii) TSP classifiers are based on gene rankings, so they are more robust to variation in technical factors or normalization than classifiers based on expression levels of individual genes. Here I describe the R package, tspair, which can be used to quickly identify and assess TSP classifiers for gene expression data. Availability: The R package tspair is freely available from Bioconductor: http://www.bioconductor.org Contact: jtleek@jhu.edu
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spelling pubmed-26726322009-04-29 The tspair package for finding top scoring pair classifiers in R Leek, Jeffrey T. Bioinformatics Applications Note Summary: Top scoring pairs (TSPs) are pairs of genes whose relative rankings can be used to accurately classify individuals into one of two classes. TSPs have two main advantages over many standard classifiers used in gene expression studies: (i) a TSP is based on only two genes, which leads to easily interpretable and inexpensive diagnostic tests and (ii) TSP classifiers are based on gene rankings, so they are more robust to variation in technical factors or normalization than classifiers based on expression levels of individual genes. Here I describe the R package, tspair, which can be used to quickly identify and assess TSP classifiers for gene expression data. Availability: The R package tspair is freely available from Bioconductor: http://www.bioconductor.org Contact: jtleek@jhu.edu Oxford University Press 2009-05-01 2009-03-10 /pmc/articles/PMC2672632/ /pubmed/19276151 http://dx.doi.org/10.1093/bioinformatics/btp126 Text en © 2009 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Note
Leek, Jeffrey T.
The tspair package for finding top scoring pair classifiers in R
title The tspair package for finding top scoring pair classifiers in R
title_full The tspair package for finding top scoring pair classifiers in R
title_fullStr The tspair package for finding top scoring pair classifiers in R
title_full_unstemmed The tspair package for finding top scoring pair classifiers in R
title_short The tspair package for finding top scoring pair classifiers in R
title_sort tspair package for finding top scoring pair classifiers in r
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2672632/
https://www.ncbi.nlm.nih.gov/pubmed/19276151
http://dx.doi.org/10.1093/bioinformatics/btp126
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