DocumentCode :
1202401
Title :
A stochastic downhill search algorithm for estimating the local false discovery rate
Author :
Scheid, Stefanie ; Spang, Rainer
Author_Institution :
Max Planck Inst. for Molecular Genetics, Berlin, Germany
Volume :
1
Issue :
3
fYear :
2004
Firstpage :
98
Lastpage :
108
Abstract :
Screening for differential gene expression in microarray studies leads to difficult large-scale multiple testing problems. The local false discovery rate is a statistical concept for quantifying uncertainty in multiple testing. We introduce a novel estimator for the local false discovery rate that is based on an algorithm which splits all genes into two groups, representing induced and noninduced genes, respectively. Starting from the full set of genes, we successively exclude genes until the gene-wise p-values of the remaining genes look like a typical sample from a uniform distribution. In comparison to other methods, our algorithm performs compatibly in detecting the shape of the local false discovery rate and has a smaller bias with respect to estimating the overall percentage of noninduced genes. Our algorithm is implemented in the Bioconductor compatible R package TWILIGHT version 1.0.1, which is available from http://compdiag.molgen.mpg.de/software or from the Bioconductor project at http://www.bioconductor.org.
Keywords :
biology computing; genetics; molecular biophysics; statistical analysis; stochastic processes; bioconductor compatible R package TWILIGHT version 1.0.1; gene expression; large-scale multiple testing; local false discovery rate; microarray studies; stochastic downhill search algorithm; Gene expression; Large-scale systems; Probability; Shape; Software algorithms; Software packages; Statistical analysis; Stochastic processes; Testing; Uncertainty; Index Terms- Local false discovery rates; biology and genetics.; microarray analysis; stochastic search algorithms; Algorithms; Computational Biology; Computer Simulation; Fusion Proteins, bcr-abl; Gene Expression Profiling; Homeodomain Proteins; Humans; Internet; Models, Statistical; Oligonucleotide Array Sequence Analysis; Oncogene Proteins, Fusion; Precursor Cell Lymphoblastic Leukemia-Lymphoma; Probability; Software; Stochastic Processes;
fLanguage :
English
Journal_Title :
Computational Biology and Bioinformatics, IEEE/ACM Transactions on
Publisher :
ieee
ISSN :
1545-5963
Type :
jour
DOI :
10.1109/TCBB.2004.24
Filename :
1377138
Link To Document :
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