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Related Experiment Video

Updated: Jul 14, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

A constrained polynomial regression procedure for estimating the local False Discovery Rate.

Cyril Dalmasso¹, Avner Bar-Hen, Philippe Broët

¹JE 2492-Univ. Paris-Sud, Villejuif, France. dalmasso@vjf.inserm.fr

BMC Bioinformatics

|July 3, 2007

Summary

A new method efficiently estimates the local False Discovery Rate (lFDR) for genomic association studies. This approach improves statistical inference for gene associations while accounting for multiple testing challenges.

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Last Updated: Jul 14, 2026

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Area of Science:

Genomics
Statistical genetics
Bioinformatics

Background:

Genomic association studies involve numerous statistical tests, necessitating methods to address multiple testing.
The local False Discovery Rate (lFDR) quantifies gene association evidence and aids in managing multiple comparisons.
lFDR provides gene-specific inferences and estimates the False Discovery Rate (FDR) for gene subsets.

Purpose of the Study:

To develop a novel and efficient procedure for estimating the local False Discovery Rate (lFDR).
To evaluate the performance of the new lFDR estimation procedure.

Main Methods:

Developed a new estimation procedure for lFDR without distributional assumptions under the alternative hypothesis.
Conducted a simulation study to compare the proposed estimator with existing methods.
Applied five different procedures, including the new one, to real biological datasets.

Main Results:

The proposed lFDR estimator demonstrated good performance in simulation studies compared to four other published methods.
The developed procedure is efficient for estimating lFDR in the context of genomic association studies.

Conclusions:

A novel and efficient procedure for estimating lFDR has been successfully developed.
The new method offers a valuable tool for analyzing genomic association studies and managing multiple testing.