Empirical null estimation using zero-inflated discrete mixture distributions and its application to protein domain data-Reference-Cited by-同舟云学术

Empirical null estimation using zero-inflated discrete mixture distributions and its application to protein domain data

Published:2017-09-22 Issue:2 Volume:74 Page:458-471
ISSN:0006-341X
Container-title:Biometrics
language:en
Short-container-title:Biom

Author:

Gauran Iris Ivy M.¹²,Park Junyong¹^ORCID,Lim Johan³,Park DoHwan¹,Zylstra John¹,Peterson Thomas⁴,Kann Maricel⁴,Spouge John L.⁵

Affiliation:

1. Department of Mathematics and Statistics; University of Maryland, Baltimore County; Baltimore Maryland 21250 U.S.A.

2. School of Statistics; University of the Philippines Diliman; Quezon City, 1101 Philippines

3. Department of Statistics; Seoul National University; Seoul, 08826 Republic of Korea

4. Department of Biological Sciences; University of Maryland, Baltimore County; Baltimore, Maryland 21250 U.S.A.

5. National Center for Biotechnology Information; National Library of Medicine; National Institutes of Health; Bethesda, Maryland 20894 U.S.A.

Publisher

Wiley

Subject

Applied Mathematics,General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,Statistics and Probability

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1111/biom.12779/fullpdf

Reference27 articles.

1. Role of proto-oncogene activation in carcinogenesis;Anderson;Environmental Health Perspectives,1992

2. Controlling the false discovery rate: A practical and powerful approach to multiple testing;Benjamini;Journal of the Royal Statistical Society,1995

3. On the generalization of Poisson distribution;Consul;The Annals of Mathematical Statistics,1970

4. Multiple hypothesis testing in microarray experiments;Dudoit;Statistical Science,2003

5. Empirical bayes analysis of a microarray experiment;Efron;Journal of the American Statistical Association,2001

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Double truncation method for controlling local false discovery rate in case of spiky null;Computational Statistics;2024-06-05

2. Individualized empirical null estimation for exact tests of healthcare quality;Statistics in Medicine;2024-04-08

3. Thresholding Gini variable importance with a single-trained random forest: An empirical Bayes approach;Computational and Structural Biotechnology Journal;2023

4. Bayesian local false discovery rate for sparse count data with application to the discovery of hotspots in protein domains;The Annals of Applied Statistics;2022-09-01

5. Thresholding Gini Variable Importance with a single trained Random Forest: An Empirical Bayes Approach;2022-04-09