A data cleaning and annotation framework for genome-wide studies

View Description

Download

small (250x250 max)

medium (500x500 max)

large ( > 500x500)

Full Resolution

you wish to report:

Your comment:

Your Name:

Submit

Cancel

...

Rights	http://www.ohsu.edu/xd/education/library/services/theses-dissertations/rights-statement.cfm
Title	A data cleaning and annotation framework for genome-wide studies
Creator.PersonalName	Ramakrishnan, Ranjani
Thesis.Degree	M.S.
Thesis.Major	Computer Science and Engineering
Thesis.DateDegreeAwarded	November 2007
Institution	Oregon Health & Science University
School	OGI School of Science & Engineering
Department	Dept. of Computer Science and Engineering
Thesis.Advisor/Mentor	McWeeney, Shannon K.
Thesis.Committee	Maier, David Erdoǧmuş, Deniz
Subject.LCSH	Genomics Bioinformatics
Subject.Keyword	Data cleaning; Annotations; Genome-wide studies; Bioinformatics; Biological data source
Call Number	Q183.5.OGISE R165 2007
Description.Abstract	Genome-wide studies are sensitive to the quality of annotation data included for analyses and they often involve overlaying both computationally derived and experimentally generated data onto a genomic scaffold. A framework for successful integration of data from diverse sources needs to address, at a minimum, the conceptualization of the biological identity in the data sources, the relationship between the sources in terms of the data present, the independence of the sources and, any discrepancies in the data. The outcome of the process should either resolve or incorporate these discrepancies into downstream analyses. In this thesis we identify factors that are important in detecting errors within and between sources and present a generalized framework to detect discrepancies. An implementation of our workflow is used to demonstrate the utility of the approach in the construction of a genome-wide mouse transcription factor binding map and in the classification of Single nucleotide polymorphisms. We also present the impact of these discrepancies on downstream analyses. The framework is extensible and we discuss future directions including summarization of the discrepancies in a biological relevant manner.
Language	eng
Type	Text
Format.Use	Needs Adobe Acrobat Reader to view.
Format.FileType	pdf
Format.FileSize	537.914 KB
OCLC number	182540403

Find results with:

Searching collections:

Home Student Scholar Archive A data cleaning and annotation framework for genome-wide studies

A data cleaning and annotation framework for genome-wide studies

Description