Literature DB >> 17634614

Comparing microarray studies.

Mayte Suárez-Fariñas1, Marcelo O Magnasco.   

Abstract

We present a practical guide to some of the issues involved in comparing or integrating different microarray studies. We discuss the influence that various factors have on the agreement between studies, such as different technologies and platforms, statistical analysis criteria, protocols, and lab variability. We discuss methods to carry out or refine such comparisons, and detail several common pitfalls to avoid. Finally, we illustrate these ideas with an example case.

Mesh:

Substances:

Year:  2007        PMID: 17634614     DOI: 10.1007/978-1-59745-390-5_8

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  8 in total

Review 1.  Advances and Trends in Omics Technology Development.

Authors:  Xiaofeng Dai; Li Shen
Journal:  Front Med (Lausanne)       Date:  2022-07-01

2.  A global meta-analysis of microarray expression data to predict unknown gene functions and estimate the literature-data divide.

Authors:  Jonathan D Wren
Journal:  Bioinformatics       Date:  2009-05-15       Impact factor: 6.937

3.  Evaluation of the psoriasis transcriptome across different studies by gene set enrichment analysis (GSEA).

Authors:  Mayte Suárez-Fariñas; Michelle A Lowes; Lisa C Zaba; James G Krueger
Journal:  PLoS One       Date:  2010-04-20       Impact factor: 3.240

4.  Pluripotency genes overexpressed in primate embryonic stem cells are localized on homologues of human chromosomes 16, 17, 19, and X.

Authors:  Ahmi Ben-Yehudah; Christopher S Navara; Carrie J Redinger; Jocelyn D Mich-Basso; Carlos A Castro; Stacie Oliver; Lara J Chensny; Thomas J Richards; Naftali Kaminski; Gerald Schatten
Journal:  Stem Cell Res       Date:  2009-09-17       Impact factor: 2.020

5.  Expanding the psoriasis disease profile: interrogation of the skin and serum of patients with moderate-to-severe psoriasis.

Authors:  Mayte Suárez-Fariñas; Katherine Li; Judilyn Fuentes-Duculan; Karen Hayden; Carrie Brodmerkel; James G Krueger
Journal:  J Invest Dermatol       Date:  2012-07-05       Impact factor: 8.551

6.  Genes and gene expression modules associated with caloric restriction and aging in the laboratory mouse.

Authors:  William R Swindell
Journal:  BMC Genomics       Date:  2009-12-07       Impact factor: 3.969

Review 7.  In praise of arrays.

Authors:  Lihua Ying; Minnie Sarwal
Journal:  Pediatr Nephrol       Date:  2008-06-21       Impact factor: 3.714

8.  MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data.

Authors:  Zhuohui Gan; Jianwu Wang; Nathan Salomonis; Jennifer C Stowe; Gabriel G Haddad; Andrew D McCulloch; Ilkay Altintas; Alexander C Zambon
Journal:  BMC Bioinformatics       Date:  2014-03-12       Impact factor: 3.169

  8 in total

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