Estimating the proportion of true null hypotheses with application in microarray data

被引:1
作者
Biswas, Aniket [1 ]
机构
[1] Dibrugarh Univ, Dept Stat, Dibrugarh 786004, Assam, India
关键词
Effect size; Expectedp-value; normality; p-value; true null; t-test; FALSE-DISCOVERY RATE; CANCER; MODEL;
D O I
10.1080/03610918.2020.1800036
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
A new formulation for the proportion of true null hypothesesbased on the sum of allp-values and the average of expectedp-values under the false null hypotheses has been proposed in the current work. This formulation of the parameter of interest pi(0) has also been used to construct a new estimator for the same. The proposed estimator removes the problem of choosing tuning parameters in the existing estimators. Though the formulation is quite general, computation of the new estimator requires use of an initial estimate of pi(0). The issue of choosing an appropriate initial estimator is also discussed in this work. The current work assumes normality for the expression level of each gene and also assumes similar tests for all the hypotheses. Simulation study shows that, the proposed estimator performs better than its closest competitor over a substantial continuous subinterval of the parameter space, under independence and weak dependence among the gene expression levels. The proposed method of estimation is applied to two real gene expression level data-sets and the results are in line with what is obtained by the competing method.
引用
收藏
页码:6294 / 6308
页数:15
相关论文
共 22 条
[1]  
[Anonymous], 2003, The Analysis of Gene Expression Data, DOI DOI 10.1007/0-387-21679
[2]   On the adaptive control of the false discovery fate in multiple testing with independent statistics [J].
Benjamini, Y ;
Hochberg, Y .
JOURNAL OF EDUCATIONAL AND BEHAVIORAL STATISTICS, 2000, 25 (01) :60-83
[3]   CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING [J].
BENJAMINI, Y ;
HOCHBERG, Y .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) :289-300
[4]   Control procedures and estimators of the false discovery rate and their application in low-dimensional settings: an empirical investigation [J].
Brinster, Regina ;
Koettgen, Anna ;
Tayo, Bamidele O. ;
Schumacher, Martin ;
Sekula, Peggy .
BMC BIOINFORMATICS, 2018, 19
[5]   Bias and variance reduction in estimating the proportion of true-null hypotheses [J].
Cheng, Yebin ;
Gao, Dexiang ;
Tong, Tiejun .
BIOSTATISTICS, 2015, 16 (01) :189-204
[6]  
Efron Bradley, 2012, Large-scale inference: empirical Bayes methods for estimation, testing, and prediction, V1
[7]   Controlling the familywise error rate with plug-in estimator for the proportion of true null hypotheses [J].
Finner, Helmut ;
Gontscharuk, Veronika .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2009, 71 :1031-1048
[8]   A stochastic process approach to false discovery control [J].
Genovese, C ;
Wasserman, L .
ANNALS OF STATISTICS, 2004, 32 (03) :1035-1061
[9]  
Gianetto QG, 2019, PACKAGE CP4P
[10]   Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring [J].
Golub, TR ;
Slonim, DK ;
Tamayo, P ;
Huard, C ;
Gaasenbeek, M ;
Mesirov, JP ;
Coller, H ;
Loh, ML ;
Downing, JR ;
Caligiuri, MA ;
Bloomfield, CD ;
Lander, ES .
SCIENCE, 1999, 286 (5439) :531-537