Title
A constrained polynomial regression procedure for estimating the local False Discovery Rate.
Abstract
In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (lFDR), which quantifies the evidence of a specific gene association with a clinical or biological variable of interest, is a relevant criterion for taking into account the multiple testing problem. The lFDR not only allows an inference to be made for each gene through its specific value, but also an estimate of Benjamini-Hochberg's False Discovery Rate (FDR) for subsets of genes.In the framework of estimating procedures without any distributional assumption under the alternative hypothesis, a new and efficient procedure for estimating the lFDR is described. The results of a simulation study indicated good performances for the proposed estimator in comparison to four published ones. The five different procedures were applied to real datasets.A novel and efficient procedure for estimating lFDR was developed and evaluated.
Year
DOI
Venue
2007
10.1186/1471-2105-8-229
BMC Bioinformatics
Keywords
Field
DocType
false discovery rate,algorithms,statistical test,bioinformatics,computer simulation,gene expression profiling,probability,regression analysis,multiple testing,polynomial regression,microarrays
False discovery rate,Empirical distribution function,Biology,Inference,Regression analysis,Polynomial regression,Multiple comparisons problem,Bioinformatics,Genetics,Gene expression profiling,Statistical hypothesis testing
Journal
Volume
Issue
ISSN
8
1
1471-2105
Citations 
PageRank 
References 
17
0.52
10
Authors
3
Name
Order
Citations
PageRank
Cyril Dalmasso1638.00
Avner Bar-Hen214812.81
Philippe Broët311918.82