An improvement of FDR for edge detection by applying EM method

被引：0

作者：

Kim, Eun-Gyoung ^{[1
]}

Kim, Sung-Ho ^{[1
]}

机构：

[1] Korea Adv Inst Sci & Technol, Dept Math Sci, Daejeon, South Korea

来源：

INTELLIGENT DATA ANALYSIS | 2022年 / 26卷 / 05期

基金：

新加坡国家研究基金会;

关键词：

Discrepancy measure; edge detection; EM algorithm; error rate; graphical Gaussian model; mixture distribution; Parzen window; EMPIRICAL BAYES; CORRELATION-COEFFICIENT; MICROARRAY; LIKELIHOOD; INFERENCE; MODELS;

D O I：

10.3233/IDA-216233

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In building a graphical model, accuracy in edge detection for the model structure is crucial for the quality of the model. We explored methods for improvement of false discovery rate(FDR) by devising an estimation procedure which is more data sensitive under some condition. The estimation is made by applying an EM method where the parameters include the density function under the null hypothesis (no edge) and the location parameters of the density functions under the alternative hypothesis (presence of edge). Our method is compared favorably with a most popular FDR tool in numerical experiments. We applied our method for analysing gene data of 800 genes and built a network of vector autoregressive model for the data.

引用

页码：1161 / 1184

页数：24

共 46 条

[31]

Miller R., 1966, SIMULTANEOUS STAT IN

[32] Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregressive process [J].

Opgen-Rhein, Rainer ;

Strimmer, Korbinian .

BMC BIOINFORMATICS, 2007, 8

[33] ON THE COMPARISON OF SEVERAL EXPERIMENTAL CATEGORIES WITH A CONTROL [J].

PAULSON, E .

ANNALS OF MATHEMATICAL STATISTICS, 1952, 23 (02) :239-246

[34] Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values [J].

Pounds, S ;

Morris, SW .

BIOINFORMATICS, 2003, 19 (10) :1236-1242

[35] An empirical Bayes approach to inferring large-scale gene association networks [J].

Schäfer, J ;

Strimmer, K .

BIOINFORMATICS, 2005, 21 (06) :754-764

[36] Diurnal changes in the transcriptome encoding enzymes of starch metabolism provide evidence for both transcriptional and posttranscriptional regulation of starch metabolism in arabidopsis leaves [J].

Smith, SM ;

Fulton, DC ;

Chia, T ;

Thorneycroft, D ;

Chapple, A ;

Dunstan, H ;

Hylton, C ;

Zeeman, SC ;

Smith, AM .

PLANT PHYSIOLOGY, 2004, 136 (01) :2687-2699

[37] A direct approach to false discovery rates [J].

Storey, JD .

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2002, 64 :479-498

[38] Statistical significance for genomewide studies [J].

Storey, JD ;

Tibshirani, R .

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2003, 100 (16) :9440-9445

[39] fdrtool: a versatile R package for estimating local and tail area-based false discovery rates [J].

Strimmer, Korbinian .

BIOINFORMATICS, 2008, 24 (12) :1461-1462

[40] Large-scale multiple testing under dependence [J].

Sun, Wenguang ;

Cai, T. Tony .

JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2009, 71 :393-424

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