Literature DB >> 12112246

Design of studies using DNA microarrays.

Richard Simon1, Michael D Radmacher, Kevin Dobbin.   

Abstract

DNA microarrays are assays that simultaneously provide information about expression levels of thousands of genes and are consequently finding wide use in biomedical research. In order to control the many sources of variation and the many opportunities for misanalysis, DNA microarray studies require careful planning. Different studies have different objectives, and important aspects of design and analysis strategy differ for different types of studies. We review several types of objectives of studies using DNA microarrays and address issues such as selection of samples, levels of replication needed, allocation of samples to dyes and arrays, sample size considerations, and analysis strategies. Copyright 2002 Wiley-Liss, Inc.

Mesh:

Year:  2002        PMID: 12112246     DOI: 10.1002/gepi.202

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  28 in total

1.  Extensive sex-specific nonadditivity of gene expression in Drosophila melanogaster.

Authors:  Greg Gibson; Rebecca Riley-Berger; Larry Harshman; Artyom Kopp; Scott Vacha; Sergey Nuzhdin; Marta Wayne
Journal:  Genetics       Date:  2004-08       Impact factor: 4.562

Review 2.  Interrogating mouse mammary cancer models: insights from gene expression profiling.

Authors:  Antonio A Fargiano; Kartiki V Desai; Jeffrey E Green
Journal:  J Mammary Gland Biol Neoplasia       Date:  2003-07       Impact factor: 2.673

Review 3.  Statistical issues in the design and analysis of gene expression microarray studies of animal models.

Authors:  Lisa M McShane; Joanna H Shih; Aleksandra M Michalowska
Journal:  J Mammary Gland Biol Neoplasia       Date:  2003-07       Impact factor: 2.673

4.  Analysis of microarray experiments of gene expression profiling.

Authors:  Adi L Tarca; Roberto Romero; Sorin Draghici
Journal:  Am J Obstet Gynecol       Date:  2006-08       Impact factor: 8.661

5.  CENP-F expression is associated with poor prognosis and chromosomal instability in patients with primary breast cancer.

Authors:  Sallyann L O'Brien; Ailís Fagan; Edward J P Fox; Robert C Millikan; Aedín C Culhane; Donal J Brennan; Amanda H McCann; Shauna Hegarty; Siobhan Moyna; Michael J Duffy; Desmond G Higgins; Karin Jirström; Göran Landberg; William M Gallagher
Journal:  Int J Cancer       Date:  2007-04-01       Impact factor: 7.396

Review 6.  Gene-expression profiling in rheumatic disease: tools and therapeutic potential.

Authors:  Jason W Bauer; Hatice Bilgic; Emily C Baechler
Journal:  Nat Rev Rheumatol       Date:  2009-05       Impact factor: 20.543

7.  Application of microarrays to identify and characterize genes involved in attachment dependence in HeLa cells.

Authors:  Pratik Jaluria; Michael Betenbaugh; Konstantinos Konstantopoulos; Bryan Frank; Joseph Shiloach
Journal:  Metab Eng       Date:  2006-12-13       Impact factor: 9.783

8.  SWISS MADE: Standardized WithIn Class Sum of Squares to evaluate methodologies and dataset elements.

Authors:  Christopher R Cabanski; Yuan Qi; Xiaoying Yin; Eric Bair; Michele C Hayward; Cheng Fan; Jianying Li; Matthew D Wilkerson; J S Marron; Charles M Perou; D Neil Hayes
Journal:  PLoS One       Date:  2010-03-26       Impact factor: 3.240

9.  Transcriptional and pathway analysis in the hypothalamus of newly hatched chicks during fasting and delayed feeding.

Authors:  Stacy E Higgins; Laura E Ellestad; Nares Trakooljul; Fiona McCarthy; Jason Saliba; Larry A Cogburn; Tom E Porter
Journal:  BMC Genomics       Date:  2010-03-09       Impact factor: 3.969

10.  Getting started in computational mass spectrometry-based proteomics.

Authors:  Olga Vitek
Journal:  PLoS Comput Biol       Date:  2009-05-29       Impact factor: 4.475

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.