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Assessing statistical significance in microarray experiments using the distance between microarrays.

Hayden D, Lazar P, Schoenfeld D, Inflammation and the Host Response to Injury Investigato - PLoS ONE (2009)

Bottom Line: We propose permutation tests based on the pairwise distances between microarrays to compare location, variability, or equivalence of gene expression between two populations.For these tests the entire microarray or some pre-specified subset of genes is the unit of analysis.The pairwise distances only have to be computed once so the procedure is not computationally intensive despite the high dimensionality of the data.

View Article: PubMed Central - PubMed

Affiliation: Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America. dhayden@partners.org

ABSTRACT
We propose permutation tests based on the pairwise distances between microarrays to compare location, variability, or equivalence of gene expression between two populations. For these tests the entire microarray or some pre-specified subset of genes is the unit of analysis. The pairwise distances only have to be computed once so the procedure is not computationally intensive despite the high dimensionality of the data. An R software package, permtest, implementing the method is freely available from the Comprehensive R Archive Network at http://cran.r-project.org.

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Principal Components
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pone-0005838-g002: Principal Components

Mentions: Figure 2 illustrates the location of the two recovery groups in the subspace spanned by the first and third principal components. Note that the same cluster of two early recovery patients (denoted by “1”) and eight late recovery patients (denoted by “2”) can be seen on the right hand side of the figure.


Assessing statistical significance in microarray experiments using the distance between microarrays.

Hayden D, Lazar P, Schoenfeld D, Inflammation and the Host Response to Injury Investigato - PLoS ONE (2009)

Principal Components
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2691999&req=5

pone-0005838-g002: Principal Components
Mentions: Figure 2 illustrates the location of the two recovery groups in the subspace spanned by the first and third principal components. Note that the same cluster of two early recovery patients (denoted by “1”) and eight late recovery patients (denoted by “2”) can be seen on the right hand side of the figure.

Bottom Line: We propose permutation tests based on the pairwise distances between microarrays to compare location, variability, or equivalence of gene expression between two populations.For these tests the entire microarray or some pre-specified subset of genes is the unit of analysis.The pairwise distances only have to be computed once so the procedure is not computationally intensive despite the high dimensionality of the data.

View Article: PubMed Central - PubMed

Affiliation: Biostatistics Center, Massachusetts General Hospital, Boston, Massachusetts, United States of America. dhayden@partners.org

ABSTRACT
We propose permutation tests based on the pairwise distances between microarrays to compare location, variability, or equivalence of gene expression between two populations. For these tests the entire microarray or some pre-specified subset of genes is the unit of analysis. The pairwise distances only have to be computed once so the procedure is not computationally intensive despite the high dimensionality of the data. An R software package, permtest, implementing the method is freely available from the Comprehensive R Archive Network at http://cran.r-project.org.

Show MeSH