Results 21 to 30 of about 385,160 (293)

Testing jumps via false discovery rate control. [PDF]

PLoS ONE, 2013
Many recently developed nonparametric jump tests can be viewed as multiple hypothesis testing problems. For such multiple hypothesis tests, it is well known that controlling type I error often makes a large proportion of erroneous rejections, and such ...
Yu-Min Yen
doaj   +1 more source

False discovery rate for functional data [PDF]

TEST, 2021
Since Benjamini and Hochberg introduced false discovery rate (FDR) in their seminal paper, this has become a very popular approach to the multiple comparisons problem. An increasingly popular topic within functional data analysis is local inference, i.e., the continuous statistical testing of a null hypothesis along the domain.
Niels Lundtorp Olsen, Alessia Pini, Simone Vantini   +2 more
openaire   +5 more sources

4497 Accessible False Discovery Rate Computation

Journal of Clinical and Translational Science, 2020
OBJECTIVES/GOALS: To improve the implementation of FDRs in translation research. Current statistical packages are hard to use and fail to adequately convey strong assumptions.
Megan C Hollister, Jeffrey D. Blume
doaj   +1 more source

BAYESIAN LOCAL FALSE DISCOVERY RATE FOR SPARSE COUNT DATA WITH APPLICATION TO THE DISCOVERY OF HOTSPOTS IN PROTEIN DOMAINS

, 2022
In cancer research at the molecular level, it is critical to understand which somatic mutations play an important role in the initiation or progression of cancer. Recently, studying cancer somatic variants at the protein domain level is an important area
Kann, Maricel G., Maricel G. Kann, Ilia Rattsev, Gauran, Iris Ivy M., Peterson, Thomas A., Park, DoHwan, Iris Ivy M. Gauran, Rattsev, Ilia, Junyong Park, Park, Junyong, Thomas A. Peterson, DoHwan Park   +11 more
core   +1 more source

2dFDR: a new approach to confounder adjustment substantially increases detection power in omics association studies

Genome Biology, 2021
One challenge facing omics association studies is the loss of statistical power when adjusting for confounders and multiple testing. The traditional statistical procedure involves fitting a confounder-adjusted regression model for each omics feature ...
Sangyoon Yi, Xianyang Zhang, Lu Yang, Jinyan Huang, Yuanhang Liu, Chen Wang, Daniel J. Schaid, Jun Chen   +7 more
doaj   +1 more source

Robust estimation of the false discovery rate [PDF]

Bioinformatics, 2006
AbstractMotivation: Presently available methods that use p-values to estimate or control the false discovery rate (FDR) implicitly assume that p-values are continuously distributed and based on two-sided tests. Therefore, it is difficult to reliably estimate the FDR when p-values are discrete or based on one-sided tests.Results: A simple and robust ...
Stan Pounds, Cheng Cheng
openaire   +2 more sources

Improving false discovery rate estimation [PDF]

Bioinformatics, 2004
Abstract Motivation: Recent attempts to account for multiple testing in the analysis of microarray data have focused on controlling the false discovery rate (FDR). However, rigorous control of the FDR at a preselected level is often impractical.
Stan Pounds, Cheng Cheng
openaire   +2 more sources

False discovery rates: a new deal [PDF]

Biostatistics, 2016
Abstract We introduce a new Empirical Bayes approach for large-scale hypothesis testing, including estimating False Discovery Rates (FDRs), and effect sizes. This approach has two key differences from existing approaches to FDR analysis.
openaire   +2 more sources

False discovery rate control in two-stage designs

BMC Bioinformatics, 2012
Background For gene expression or gene association studies with a large number of hypotheses the number of measurements per marker in a conventional single-stage design is often low due to limited resources.
Zehetmayer Sonja, Posch Martin
doaj   +1 more source

High-throughput analysis suggests differences in journal false discovery rate by subject area and impact factor but not open access status

BMC Bioinformatics, 2020
Background A low replication rate has been reported in some scientific areas motivating the creation of resource intensive collaborations to estimate the replication rate by repeating individual studies.
L. M. Hall, A. E. Hendricks
doaj   +1 more source