SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures

HQ Wang, LK Tuominen, CJ Tsai - Bioinformatics, 2011 - academic.oup.com
Motivation: The pre-estimate of the proportion of null hypotheses (π0) plays a critical role in
controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden …
被引用次数：242 相关文章

SLIM

HQ Wang, LK Tuominen, CJ Tsai - Bioinformatics, 2011 - dl.acm.org
Motivation: The pre-estimate of the proportion of null hypotheses (π0) plays a critical role in
controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden …

SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures.

HQ Wang, LK Tuominen, CJ Tsai - Bioinformatics (Oxford, England), 2010 - europepmc.org
Results From the basic non-linear model of the q-value method, we developed a simple
linear algorithm to probe local dependence blocks. We uncovered a non-static relationship …
[PDF] researchgate.net

[PDF][PDF] SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures

HQ Wang, LK Tuominen, CJ Tsai - 2010 - researchgate.net
Motivation: The pre-estimate of the proportion of null hypotheses (π0) plays a critical role in
controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden …
[PDF] psu.edu

[PDF][PDF] SLIM: A Sliding Linear Model for Estimating the Proportion of True Null Hypotheses in Datasets With Dependence Structures

HQ Wang, LK Tuominen, CJ Tsai - 2010 - Citeseer
Motivation: The pre-estimate of the proportion of null hypotheses (0 π) plays a critical role in
controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden …
[PDF] academia.edu

[PDF][PDF] SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures

HQ Wang, LK Tuominen, CJ Tsai - 2010 - academia.edu
Motivation: The pre-estimate of the proportion of null hypotheses (π0) plays a critical role in
controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden …

SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures

HQ Wang, LK Tuominen… - Bioinformatics (Oxford …, 2011 - pubmed.ncbi.nlm.nih.gov
Motivation The pre-estimate of the proportion of null hypotheses (π (0)) plays a critical role in
controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden …

[引用][C] SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures

HQ WANG, LK TUOMINEN… - Bioinformatics (Oxford …, 2011 - pascal-francis.inist.fr
SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets
with dependence structures CNRS Inist Pascal-Francis CNRS Pascal and Francis …
[PDF] archive.org

[PDF][PDF] SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures

HQ Wang, LK Tuominen, CJ Tsai - 2010 - scholar.archive.org
Motivation: The pre-estimate of the proportion of null hypotheses (π0) plays a critical role in
controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden …

SLIM: a sliding linear model for estimating the proportion of true null hypotheses in datasets with dependence structures.

HQ Wang, LK Tuominen, CJ Tsai - Bioinformatics, 2011 - search.ebscohost.com
Motivation: The pre-estimate of the proportion of null hypotheses (π0) plays a critical role in
controlling false discovery rate (FDR) in multiple hypothesis testing. However, hidden …