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The proportion of true null hypothes...

Markitsis, Anastasios.

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The proportion of true null hypotheses in microarray gene expression data.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The proportion of true null hypotheses in microarray gene expression data./
Author:	Markitsis, Anastasios.
Description:	135 p.
Notes:	Source: Dissertation Abstracts International, Volume: 71-04, Section: B, page: 2470.
Contained By:	Dissertation Abstracts International71-04B.
Subject:	Biology, Biostatistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3397570
ISBN:	9781109695618

The proportion of true null hypotheses in microarray gene expression data.
Markitsis, Anastasios.

The proportion of true null hypotheses in microarray gene expression data. - 135 p.

Source: Dissertation Abstracts International, Volume: 71-04, Section: B, page: 2470.

Thesis (Ph.D.)--The George Washington University, 2010.

Microarray technology is extensively used today in many applications. One of its uses is discovering sets of genes that are most likely to be related to cancer. Typically, based on microarray data, a statistical test is conducted for each of thousands of genes simultaneously. In a two-group comparative microarray experiment, an important parameter for controlling the rate of false positives and also for determining the appropriate sample size is the proportion of true null hypotheses (pi0).

ISBN: 9781109695618Subjects--Topical Terms:

1018416
Biology, Biostatistics.

The proportion of true null hypotheses in microarray gene expression data.
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020 $a 9781109695618
035 $a (UMI)AAI3397570
035 $a AAI3397570
040 $a UMI $c UMI
100 1 $a Markitsis, Anastasios. $3 1669077
245 1 4 $a The proportion of true null hypotheses in microarray gene expression data.
300 $a 135 p.
500 $a Source: Dissertation Abstracts International, Volume: 71-04, Section: B, page: 2470.
500 $a Adviser: Yinglei Lai.
502 $a Thesis (Ph.D.)--The George Washington University, 2010.
520 $a Microarray technology is extensively used today in many applications. One of its uses is discovering sets of genes that are most likely to be related to cancer. Typically, based on microarray data, a statistical test is conducted for each of thousands of genes simultaneously. In a two-group comparative microarray experiment, an important parameter for controlling the rate of false positives and also for determining the appropriate sample size is the proportion of true null hypotheses (pi0).
520 $a To obtain an improved estimation method for pi0, we modify an existing simple method by introducing artificial censoring to p-values. The model is a two-component mixture of a censored Uniform(0,1) and a censored Beta(alpha,1) distribution. The model fitting is achieved through the Expectation Maximization algorithm. In a comprehensive simulation study and applications to experimental data sets, we illustrate the benefits of using our method by comparing its performance to other existing methods.
520 $a Furthermore, we develop and study the properties of a likelihood ratio test for pi0 at different combinations of sample size, number of genes, and H0 value of pi0. Maximization of the restricted likelihood is achieved by incorporating a linear constraint of the parameters into the Expectation Maximization algorithm. The p-value of the test is based on a parametric bootstrap approach. We illustrate the usefulness of the test through applications to experimental datasets.
590 $a School code: 0075.
650 4 $a Biology, Biostatistics. $3 1018416
650 4 $a Statistics. $3 517247
690 $a 0308
690 $a 0463
710 2 $a The George Washington University. $b Statistics. $3 1272926
773 0 $t Dissertation Abstracts International $g 71-04B.
790 1 0 $a Lai, Yinglei, $e advisor
790 1 0 $a Li, Zhaohai $e committee member
790 1 0 $a Pan, Qing $e committee member
790 1 0 $a Stroud, Jonathan $e committee member
790 1 0 $a Tadesse, Mahlet $e committee member
790 $a 0075
791 $a Ph.D.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3397570