A simulation-based approach for evaluating microarray analyses.
The biological complexity of gene expression makes simulation of gene expression data difficult. We propose a spike-in simulation that adds a single simulated gene to the data set of interest. Features of this spike-in gene may be manipulated to observe how often the spiked-in gene appears in the list of differentially expressed genes. This approach provides insight into the data analysis method, the observed data, and the manner in which the method and data interact without relying on indefensible assumptions regarding gene coexpression.
Blades
Natalie J
NJ
Department of Statistics, Brigham Young University, Provo, UT 84602, USA. blades@stat.byu.edu
Grimshaw
Scott D
SD
Pendleton
Carly R
CR
D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D020869:Gene Expression Profiling / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*