Statistical considerations for analysis of microarray experiments.

TitleStatistical considerations for analysis of microarray experiments.
Publication TypeJournal Article
Year of Publication2011
AuthorsOwzar, Kouros, William T. Barry, and Sin-Ho Jung
JournalClin Transl Sci
Volume4
Issue6
Pagination466-77
Date Published2011 Dec
ISSN1752-8062
KeywordsAlgorithms, Clinical Trials as Topic, Computational Biology, Gene Expression Profiling, Gene Expression Regulation, Leukemic, Gene Expression Regulation, Neoplastic, Genetic Markers, Humans, Leukemia, Lung Neoplasms, Models, Statistical, Oligonucleotide Array Sequence Analysis, Phenotype, Prognosis, Software
Abstract

Microarray technologies enable the simultaneous interrogation of expressions from thousands of genes from a biospecimen sample taken from a patient. This large set of expressions generates a genetic profile of the patient that may be used to identify potential prognostic or predictive genes or genetic models for clinical outcomes. The aim of this article is to provide a broad overview of some of the major statistical considerations for the design and analysis of microarrays experiments conducted as correlative science studies to clinical trials. An emphasis will be placed on how the lack of understanding and improper use of statistical concepts and methods will lead to noise discovery and misinterpretation of experimental results.

DOI10.1111/j.1752-8062.2011.00309.x
Alternate JournalClin Transl Sci
Original PublicationStatistical considerations for analysis of microarray experiments.
PubMed ID22212230
PubMed Central IDPMC3906917
Grant ListUL1 RR024128 / RR / NCRR NIH HHS / United States
U19 AI067798 / AI / NIAID NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
RR024128 / RR / NCRR NIH HHS / United States
CA142538 / CA / NCI NIH HHS / United States
Project: