Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values.
BACKGROUND
The occurrence of false positives and false negatives in a microarray analysis could be easily estimated if the distribution of p-values were approximated and then expressed as a mixture of null and alternative densities. Essentially any distribution of p-values can be expressed as such a mixture by extracting a uniform density from it.


RESULTS
The occurrence of false positives and false negatives in a microarray analysis could be easily estimated if the distribution of p-values were approximated and then expressed as a mixture of null and alternative densities. Essentially any distribution of p-values can be expressed as such a mixture by extracting a uniform density from it.


BACKGROUND
An S-plus function library is available from http://www.stjuderesearch.org/statistics.
Pounds
Stan
S
Department of Biostatistics, St. Jude Children's Research Hospital, 332 N. Lauderdale St., Memphis, TN 38105-2794, USA. stanley.pounds@stjude.org
Morris
Stephan W
SW
D048868:Adaptor Proteins, Signal Transducing; D000465:Algorithms; D000818:Animals; D000074018:B-Cell CLL-Lymphoma 10 Protein; D001402:B-Lymphocytes / Q000378:metabolism; D005188:False Negative Reactions; D005189:False Positive Reactions; D020869:Gene Expression Profiling / Q000379:methods*; D051379:Mice; D009363:Neoplasm Proteins / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011786:Quality Control; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment; D017421:Sequence Analysis / Q000379:methods*
D048868:Adaptor Proteins, Signal Transducing; D000074018:B-Cell CLL-Lymphoma 10 Protein; C488088:Bcl10 protein, mouse; D009363:Neoplasm Proteins