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Statistical Methods for Next Generat...

Zhang, Miao.

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Statistical Methods for Next Generation Sequencing Data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical Methods for Next Generation Sequencing Data./
Author:	Zhang, Miao.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
Description:	81 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-04, Section: B.
Contained By:	Dissertations Abstracts International80-04B.
Subject:	Statistics. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10931857
ISBN:	9780438562226

Statistical Methods for Next Generation Sequencing Data.
Zhang, Miao.

Statistical Methods for Next Generation Sequencing Data. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 81 p.

Source: Dissertations Abstracts International, Volume: 80-04, Section: B.

Thesis (Ph.D.)--The University of Arizona, 2018.

This item must not be added to any third party search indexes.

Statistical genetics is a scientific field concerned with the development of statistical methods for drawing inferences from genetic data. Research in statistical genetics generally involves developing theory or methodology to support research in one of three related areas: population genetics, genetic epidemiology and quantitative genetics. This dissertation is an ensemble of my research work in statistical genetics, including three projects with varying focuses. The first project applies a rare variant region-based test to identify sets of common or rare variants aggregated in and around genes associated with Dravet Syndrome. The second project proposes a score-based test to investigate the association for a set of rare variants and ordinal traits. The third project describes an implement of dimensionality reduction method in genotype data for population inference.

ISBN: 9780438562226Subjects--Topical Terms:

517247
Statistics.
Subjects--Index Terms:

Sequencing data

Statistical Methods for Next Generation Sequencing Data.
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300 $a 81 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-04, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Watkins, Joseph C.;Zhou, Jin.
502 $a Thesis (Ph.D.)--The University of Arizona, 2018.
506 $a This item must not be added to any third party search indexes.
506 $a This item must not be sold to any third party vendors.
520 $a Statistical genetics is a scientific field concerned with the development of statistical methods for drawing inferences from genetic data. Research in statistical genetics generally involves developing theory or methodology to support research in one of three related areas: population genetics, genetic epidemiology and quantitative genetics. This dissertation is an ensemble of my research work in statistical genetics, including three projects with varying focuses. The first project applies a rare variant region-based test to identify sets of common or rare variants aggregated in and around genes associated with Dravet Syndrome. The second project proposes a score-based test to investigate the association for a set of rare variants and ordinal traits. The third project describes an implement of dimensionality reduction method in genotype data for population inference.
590 $a School code: 0009.
650 4 $a Statistics. $3 517247
653 $a Sequencing data
653 $a Statistical methods
690 $a 0463
710 2 $a The University of Arizona. $b Statistics. $3 3180378
773 0 $t Dissertations Abstracts International $g 80-04B.
790 $a 0009
791 $a Ph.D.
792 $a 2018
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10931857