Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 362922
Title Analysis of the real EADGENE data set: Multivariate approaches and post analyis
Author(s) Sorensen, P.; Bonnet, A.; Buitenhuis, B.; Closset, R.; Dejean, S.; Delmas, C.; Duval, M.; Glass, L.; Hedegaard, J.; Hornshoj, H.; Hulsegge, B.; Jaffrezic, F.; Jensen, K.; Jiang, L.; Koning, D.J. de; Lê Cao, K.A.; Nie, H.; Petzl, W.; Pool, M.H.; Robert-Granie, C.; San Cristobal, M.; Lund, M.S.; Schothorst, E.M. van; Schuberth, H.J.; Seyfert, H.M.; Tosser-klopp, G.; Waddington, D.; Watson, D.; Yang, W.; Zerbe, H.
Source Genetics, Selection, Evolution 39 (2007)6. - ISSN 0999-193X - p. 651 - 668.
Department(s) Livestock Research
Animal Breeding and Genetics
RIKILT - Business Unit Safety & Health
Publication type Refereed Article in a scientific journal
Publication year 2007
Keyword(s) gene-expression data - escherichia-coli - bioconductor - association - biology
Abstract The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. Several teams used hierarchical clustering (HC) or principal component analysis (PCA) to identify groups of differentially expressed genes with a similar expression pattern over time points and infective agent (E. coli or S. aureus). The main result from these analyses was that HC and PCA were able to separate tissue samples taken at 24 h following E. coli infection from the other samples. The second approach identified groups of differentially co-expressed genes, by identifying clusters of genes highly correlated when animals were infected with E. coli but not correlated more than expected by chance when the infective pathogen was S. aureus. The third approach looked at differential expression of predefined gene sets. Gene sets were defined based on information retrieved from biological databases such as Gene Ontology. Based on these annotation sources the teams used either the GlobalTest or the Fisher exact test to identify differentially expressed gene sets. The main result from these analyses was that gene sets involved in immune defence responses were differentially expressed.
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