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1.
Genet Sel Evol ; 39(6): 621-31, 2007.
Article in English | MEDLINE | ID: mdl-18053572

ABSTRACT

Microarray analyses have become an important tool in animal genomics. While their use is becoming widespread, there is still a lot of ongoing research regarding the analysis of microarray data. In the context of a European Network of Excellence, 31 researchers representing 14 research groups from 10 countries performed and discussed the statistical analyses of real and simulated 2-colour microarray data that were distributed among participants. The real data consisted of 48 microarrays from a disease challenge experiment in dairy cattle, while the simulated data consisted of 10 microarrays from a direct comparison of two treatments (dye-balanced). While there was broader agreement with regards to methods of microarray normalisation and significance testing, there were major differences with regards to quality control. The quality control approaches varied from none, through using statistical weights, to omitting a large number of spots or omitting entire slides. Surprisingly, these very different approaches gave quite similar results when applied to the simulated data, although not all participating groups analysed both real and simulated data. The workshop was very successful in facilitating interaction between scientists with a diverse background but a common interest in microarray analyses.


Subject(s)
Oligonucleotide Array Sequence Analysis/statistics & numerical data , Animals , Animals, Domestic/genetics , Cattle , Computer Simulation , Data Interpretation, Statistical , Escherichia coli Infections/genetics , Escherichia coli Infections/veterinary , Europe , Female , Gene Expression Profiling/standards , Gene Expression Profiling/statistics & numerical data , Host-Pathogen Interactions/genetics , Mastitis, Bovine/genetics , Oligonucleotide Array Sequence Analysis/standards , Quality Control , Staphylococcal Infections/genetics , Staphylococcal Infections/veterinary
2.
Genet Sel Evol ; 39(6): 633-50, 2007.
Article in English | MEDLINE | ID: mdl-18053573

ABSTRACT

A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.


Subject(s)
Databases, Genetic , Gene Expression Profiling/statistics & numerical data , Oligonucleotide Array Sequence Analysis/statistics & numerical data , Analysis of Variance , Animals , Animals, Domestic/genetics , Bias , Cattle/genetics , Data Interpretation, Statistical , Escherichia coli Infections/genetics , Escherichia coli Infections/veterinary , Europe , Female , Gene Expression Profiling/standards , Guidelines as Topic , Mastitis, Bovine/genetics , Oligonucleotide Array Sequence Analysis/standards , Quality Control , Software , Staphylococcal Infections/genetics , Staphylococcal Infections/veterinary
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