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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.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	The proportion of true null hypotheses in microarray gene expression data./
作者:	Markitsis, Anastasios.
面頁冊數:	135 p.
附註:	Source: Dissertation Abstracts International, Volume: 71-04, Section: B, page: 2470.
Contained By:	Dissertation Abstracts International71-04B.
標題:	Biology, Biostatistics. -
電子資源:	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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245 1 4 $a The proportion of true null hypotheses in microarray gene expression data.
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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.
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650 4 $a Statistics. $3 517247
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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
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791 $a Ph.D.
792 $a 2010
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