A constrained polynomial regression procedure for estimating the local False Discovery Rate
<p>Abstract</p> <p>Background</p> <p>In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (<it>lFDR</it>), which quantifies the evidence of a specific gene a...
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doaj-2edef9b9918041c79c258b4516e6db122020-11-24T21:28:34ZengBMCBMC Bioinformatics1471-21052007-06-018122910.1186/1471-2105-8-229A constrained polynomial regression procedure for estimating the local False Discovery RateBroët PhilippeBar-Hen AvnerDalmasso Cyril<p>Abstract</p> <p>Background</p> <p>In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (<it>lFDR</it>), 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 <it>lFDR </it>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 (<it>FDR</it>) for subsets of genes.</p> <p>Results</p> <p>In the framework of estimating procedures without any distributional assumption under the alternative hypothesis, a new and efficient procedure for estimating the <it>lFDR </it>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.</p> <p>Conclusion</p> <p>A novel and efficient procedure for estimating <it>lFDR </it>was developed and evaluated.</p> http://www.biomedcentral.com/1471-2105/8/229 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Broët Philippe Bar-Hen Avner Dalmasso Cyril |
spellingShingle |
Broët Philippe Bar-Hen Avner Dalmasso Cyril A constrained polynomial regression procedure for estimating the local False Discovery Rate BMC Bioinformatics |
author_facet |
Broët Philippe Bar-Hen Avner Dalmasso Cyril |
author_sort |
Broët Philippe |
title |
A constrained polynomial regression procedure for estimating the local False Discovery Rate |
title_short |
A constrained polynomial regression procedure for estimating the local False Discovery Rate |
title_full |
A constrained polynomial regression procedure for estimating the local False Discovery Rate |
title_fullStr |
A constrained polynomial regression procedure for estimating the local False Discovery Rate |
title_full_unstemmed |
A constrained polynomial regression procedure for estimating the local False Discovery Rate |
title_sort |
constrained polynomial regression procedure for estimating the local false discovery rate |
publisher |
BMC |
series |
BMC Bioinformatics |
issn |
1471-2105 |
publishDate |
2007-06-01 |
description |
<p>Abstract</p> <p>Background</p> <p>In the context of genomic association studies, for which a large number of statistical tests are performed simultaneously, the local False Discovery Rate (<it>lFDR</it>), 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 <it>lFDR </it>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 (<it>FDR</it>) for subsets of genes.</p> <p>Results</p> <p>In the framework of estimating procedures without any distributional assumption under the alternative hypothesis, a new and efficient procedure for estimating the <it>lFDR </it>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.</p> <p>Conclusion</p> <p>A novel and efficient procedure for estimating <it>lFDR </it>was developed and evaluated.</p> |
url |
http://www.biomedcentral.com/1471-2105/8/229 |
work_keys_str_mv |
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