Paper Info
Title
Stability of gene contributions and identification of outliers in multivariate analysis of microarray data.
Abstract
Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages compared to common gene-by-gene approaches. However, due to their exploratory nature, multivariate ordination methods do not allow direct statistical testing of the stability of genes.In this study, we developed a computationally efficient algorithm for: i) the assessment of the significance of gene contributions and ii) the identification of sample outliers in multivariate analysis of microarray data. The approach is based on the use of resampling methods including bootstrapping and jackknifing. A statistical package of R functions was developed. This package includes tools for both inferring the statistical significance of gene contributions and identifying outliers among samples.The methodology was successfully applied to three published data sets with varying levels of signal intensities. Its relevance was compared with alternative methods. Overall, it proved to be particularly effective for the evaluation of the stability of microarray data.
Year
DOI
Venue
2008
10.1186/1471-2105-9-289
BMC Bioinformatics
Keywords
Field
DocType
bioinformatics,microarrays,complex data,microarray data,genomic instability,proteome,statistical significance,statistical test,algorithms,gene expression profiling,multivariate analysis
Data mining,Biology,Multivariate statistics,Ordination,Outlier,Microarray analysis techniques,Bioinformatics,Multivariate analysis,DNA microarray,Statistical hypothesis testing,Gene expression profiling
Journal
Volume
Issue
ISSN
9
1
1471-2105
Citations 
PageRank 
References 
27
0.54
5
Authors
5
Name
Order
Citations
PageRank
Florent Baty1873.53
Daniel Jaeger2300.95
Frank Preiswerk3777.16
Martin M Schumacher4644.16
Martin Brutsche5873.53