A permutation test for determining significance of clusters with applications to spatial and gene expression data.
Peter J. ParkJ. ManjouridesMarco BonettiMarcello PaganoPublished in: Comput. Stat. Data Anal. (2009)
Keyphrases
- gene expression data
- permutation tests
- analysis of gene expression data
- microarray
- gene expression
- statistical significance
- data sets
- microarray data
- cross validation
- gene expression analysis
- statistical inference
- high dimensionality
- class imbalance
- gene selection
- high dimensional
- feature selection
- gene clusters
- genomic data
- cluster analysis
- statistically significant
- clustering algorithm
- high throughput
- gene expression profiles
- high dimensional data
- biological data
- dimensionality reduction
- transcription factors
- model selection
- null hypothesis
- machine learning