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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Assessing Statistical Significance in Microarray Experiments Using the Distance Between Microarrays

ABSTRACT: We propose a method to compare the location and variability of gene ex-pression between two groups of microarrays using a permutation test based on the pairwise distance between microarrays. The microarrays could be samples from distinct clinical or biological populations or microarrays prepared at two different levels of an experimental factor. For these tests the entire microarray or some pre-specifed subset of genes, not the individual gene, is the unit of analysis. We apply this method to compare results from two dfferent protocols for preparing labeled targets for microarray hybridization and their subsequent gene expression analysis. Keywords: Comparative genomic expression Overall design - Splenocytes were extracted from six sham mice and six trauma-hemorrhagic mice. Total RNA was prepared from individual mice and labeled as targets by two different methods for analysis on Affymentrix MOE 430 2+chips.

ORGANISM(S): Mus musculus

SUBMITTER: IDDC Inflammation & the Host Response to Injury

PROVIDER: E-GEOD-9424 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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

Hayden Douglas D Lazar Peter P Schoenfeld David D

PloS one 20090616 6

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 ...[more]

PMID: 19529777

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Assessing Statistical Significance in Microarray Experiments Using the Distance Between Microarrays

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