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.
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%0 Journal Article
%1 Owzar2011
%A Owzar, Kouros
%A Barry, William T
%A Jung, Sin-Ho
%D 2011
%J Clinical and translational science
%K Algorithms ClinicalTrialsasTopic ComputationalBiology ComputationalBiology:methods GeneExpressionProfiling GeneExpressionRegulation GeneticMarkers GeneticMarkers:genetics Humans Leukemia Leukemia:metabolism Leukemic LungNeoplasms LungNeoplasms:diagnosis LungNeoplasms:metabolism Models Neoplastic OligonucleotideArraySequenceAnalysis OligonucleotideArraySequenceAnalysis:methods Phenotype Prognosis Software Statistical
%N 6
%P 466-77
%R 10.1111/j.1752-8062.2011.00309.x
%T Statistical considerations for analysis of microarray experiments.
%U http://dx.doi.org/10.1111/j.1752-8062.2011.00309.x http://www.ncbi.nlm.nih.gov/pubmed/22212230
%V 4
%X 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.
%@ 1752-8062
@article{Owzar2011,
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.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Owzar, Kouros and Barry, William T and Jung, Sin-Ho},
biburl = {https://www.bibsonomy.org/bibtex/28e535f342cdd5c15932ca8a7ce002187/jepcastel},
doi = {10.1111/j.1752-8062.2011.00309.x},
interhash = {b90bbb0eed586fa9a284493d4467d608},
intrahash = {8e535f342cdd5c15932ca8a7ce002187},
isbn = {1752-8062},
issn = {1752-8062},
journal = {Clinical and translational science},
keywords = {Algorithms ClinicalTrialsasTopic ComputationalBiology ComputationalBiology:methods GeneExpressionProfiling GeneExpressionRegulation GeneticMarkers GeneticMarkers:genetics Humans Leukemia Leukemia:metabolism Leukemic LungNeoplasms LungNeoplasms:diagnosis LungNeoplasms:metabolism Models Neoplastic OligonucleotideArraySequenceAnalysis OligonucleotideArraySequenceAnalysis:methods Phenotype Prognosis Software Statistical},
month = {12},
note = 6405,
number = 6,
pages = {466-77},
pmid = {22212230},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {Statistical considerations for analysis of microarray experiments.},
url = {http://dx.doi.org/10.1111/j.1752-8062.2011.00309.x http://www.ncbi.nlm.nih.gov/pubmed/22212230},
volume = 4,
year = 2011
}