Fold change and p-value cutoffs significantly alter microarray interpretations.
Mark R. DalmanAnthony DeeterGayathri NimishakaviZhong-Hui DuanPublished in: BMC Bioinform. (2012)
Keyphrases
- microarray
- gene expression
- high throughput
- gene expression data
- microarray data
- gene ontology
- gene expression profiling
- microarray data analysis
- high dimensionality
- molecular biology
- gene selection
- gene networks
- clustering analysis
- gene expression analysis
- experimental conditions
- microarray images
- dna microarray
- gene expression profiles
- regulatory networks
- gene expression datasets
- gene expression levels
- gene expression data sets
- cancer classification
- yeast cell cycle
- microarray expression data
- machine learning
- colon cancer
- differentially expressed genes
- gene expression microarray data
- cdna microarray
- tissue samples
- gene expression patterns
- cancer diagnosis
- biological processes
- genome wide
- biological networks
- high dimensional
- data analysis