====== kerfdr ======

The use in Biology of current high-throughput genetic and post-genomic data leads to the simultaneous evaluation of a huge number of statistical hypothesis and at the same time, to the multiple-testing problem. As an alternative to the too conservative Family-Wise Error-Rate (FWER), the **False Discovery Rate** (FDR) has appeared for the last ten years as the more appropriate criterion to handle the problem. One drawback is that the FDR is associated to a given rejection region for the statistic considered, without distinguishing those that are close to the boundary and those that are not.

As a result, the **local FDR** has been recently proposed to quantifies the specific probability, given the p-value, for being under the null hypothesis. In this context we present a **semi-parametric approach** based on **kernel** estimators.

    * kerfdr: {{:logiciels:kerfdr.r|source}}, {{:logiciels:kerfdr_1.0.2.zip|package}}, {{:logiciels:kerfdr-manual.pdf|RDoc}}, {{:logiciels:kerfdrpseudocode.pdf|pseudo-code}}
    * [[http://cran.at.r-project.org/web/packages/kerfdr/index.html|kerfdr on CRAN]]

 

{{:logiciels:kerfdr.png}}

** Publications **

    * kerfdr: A semi-parametric kernel-based approach to local FDR estimations. Guedj, Célisse, Robin and Nuel. //BMC Bioinformatics//. 2009. 10:84. [[http://www.biomedcentral.com/1471-2105/10/84|link]]

    * A semi-parametric approach for mixture models: application to local false discovery rate estimation. Robin, Bar-Hen et al. //Comput. Statist. and Data Analysis//. 2007. 51: 5483-5493. [[http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V8V-4N7RW3X-1&_user=801326&_coverDate=08%2F15%2F2007&_rdoc=6&_fmt=summary&_orig=browse&_srch=doc-info(%23toc%235880%232007%23999489987%23664218%23FLA%23display%23Volume)&_cdi=5880&_sort=d&_docanchor=&view=c&_ct=92&_acct=C000043739&_version=1&_urlVersion=0&_userid=801326&md5=89d8cecd47d3bc8f3e019f92347b23c2|abstract]]


**Talk**
 
    * kerfdr: A semi-parametric kernel-based approach to local FDR estimation. Guedj et al. //Statistical Methods for Post-Genomics Data 2008//, Rennes. {{:logiciels:slideskerfdr.pdf|slides}}

**Poster**

    * kerfdr: A semi-parametric kernel-based approach for local FDR estimations. Nuel, Guedj et al. //IGES 2007, York (UK)//. {{:logiciels:kerfdr_postera4.pdf|poster}}

 

This work is the result of the [[http://www.ssbgroup.fr|SSB group]].