Review reveals common flaws in microarray gene-expression studies

2007 ◽  
Keyword(s):  
Gene Expression ◽  
Microarray Gene Expression ◽  
Expression Studies ◽  
Microarray Gene ◽  
Gene Expression Studies

A combined analysis of microarray gene expression studies of the human prefrontal cortex identifies genes implicated in schizophrenia

2012 ◽  
Vol 46 (11) ◽  
pp. 1464-1474 ◽  
Author(s):  
Josué Pérez-Santiago ◽  
Rebeca Diez-Alarcia ◽  
Luis F. Callado ◽  
Jin X. Zhang ◽  
Gursharan Chana ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prefrontal Cortex ◽  
Microarray Gene Expression ◽  
Combined Analysis ◽  
Expression Studies ◽  
Microarray Gene ◽  
Gene Expression Studies

Meta-analysis of microarray gene expression studies on intracranial aneurysms

Neuroscience ◽  
2012 ◽  
Vol 201 ◽  
pp. 105-113 ◽  
Author(s):  
C. Roder ◽  
H. Kasuya ◽  
A. Harati ◽  
M. Tatagiba ◽  
I. Inoue ◽  
...  
Keyword(s):  
Gene Expression ◽  
Intracranial Aneurysms ◽  
Meta Analysis ◽  
Microarray Gene Expression ◽  
Expression Studies ◽  
Microarray Gene ◽  
Gene Expression Studies

scholarly journals Automatic module selection from several microarray gene expression studies

Biostatistics ◽  
2017 ◽  
Vol 19 (2) ◽  
pp. 153-168
Author(s):  
Alix Zollinger ◽  
Anthony C Davison ◽  
Darlene R Goldstein
Keyword(s):  
Gene Expression ◽  
Microarray Gene Expression ◽  
Expression Studies ◽  
Module Selection ◽  
Microarray Gene ◽  
Gene Expression Studies

Sample Selection for Microarray Gene Expression Studies

2005 ◽  
Vol 44 (03) ◽  
pp. 461-467 ◽  
Author(s):  
D. Repsilber ◽  
L. Fink ◽  
M. Jacobsen ◽  
O. Bläsing ◽  
A. Ziegler
Keyword(s):  
Gene Expression ◽  
Study Groups ◽  
Case Control Studies ◽  
Microarray Gene Expression ◽  
Microarray Experiments ◽  
Expression Studies ◽  
Microarray Gene ◽  
Gene Expression Studies ◽  
Microarray Studies ◽  
Study Base

Summary Objectives: The choice of biomedical samples for microarray gene expression studies is decisive for both validity and interpretability of results. We present a consistent, comprehensive framework to deal with the typical selection problems in microarray studies. Methods: Microarray studies are designed either as case-control studies or as comparisons of parallel groups from cohort studies, since high levels of random variation in the experimental approach thwart absolute measurements of gene expression levels. Validity and results of gene expression studies heavily rely on the appropriate choice of these study groups. Therefore, the so-called principles of comparability, which are well known from both clinical and epidemiological studies, need to be applied to microarray experiments. Results: The principles of comparability are the study-base principle, the principle of deconfounding and the principle of comparable accuracy in measurements. We explain each of these principles, show how they apply to microarray experiments, and illustrate them with examples. The examples are chosen as to represent typical stumbling blocks of microarray experimental design, and to exemplify the benefits of implementing the principles of comparability in the setting of micro-array experiments. Conclusions: Microarray studies are closely related to classical study designs and therefore have to obey the same principles of comparability as these. Their validity should not be compromised by selection, confounding or information bias. The so-called study-base principle, calling for comparability and thorough definition of the compared cell populations, is the key principle for the choice of biomedical samples and controls in microarray studies.

A design and statistical perspective on microarray gene expression studies in nutrition:

Nutrition ◽  
2003 ◽  
Vol 19 (11-12) ◽  
pp. 997-1000 ◽  
Author(s):  
Grier P Page ◽  
Jode W Edwards ◽  
Stephen Barnes ◽  
Richard Weindruch ◽  
David B Allison
Keyword(s):  
Gene Expression ◽  
Microarray Gene Expression ◽  
Expression Studies ◽  
Microarray Gene ◽  
Gene Expression Studies
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