Statistical methods in genomics research Journal Article


Authors: Satagopan, J. M.; Smith, A. D.
Article Title: Statistical methods in genomics research
Abstract: Recent advances in marker technologies have led to increasing interest in and investigation on the role of genetic alterations in disease etiology and progression. Allelic or mutational data are used in linkage disequilibrium (i.e., association) studies to identify genes conferring disease risk. The extent of risk conferred by these genetic loci can be immensely useful for disease prevention initiatives and population-based medical intervention. Lately, gene microarrays are used to compare expression levels in different types of diseases, with the goal to identify genes involved in causal or functional pathways leading to tumor or tumor progression. Statistical methods are intrinsic to the successful design of these studies, analysis of the resulting data, and interpretation of the results. This paper provides a brief introductory summary to some of the commonly used statistical methods in genetic studies. Copyright © 2003 S. Karger AG, Basel.
Keywords: disease course; pathogenesis; review; gene expression; gene locus; linkage disequilibrium; risk factor; gene mapping; population research; statistical analysis; prophylaxis; gene identification; data analysis; genomics; dna microarray; tumor growth; gene linkage disequilibrium; disease risk; human; priority journal; multiple testing
Journal Title: HeartDrug
Volume: 3
Issue: 1
ISSN: 1422-9528
Publisher: S. Karger AG  
Date Published: 2003-01-01
Start Page: 48
End Page: 60
Language: English
DOI: 10.1159/000070907
PROVIDER: scopus
DOI/URL:
Notes: Export Date: 25 September 2014 -- Source: Scopus
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  1. Jaya M Satagopan
    141 Satagopan
  2. Alexander D Smith
    28 Smith