ReviewSeminars in cancer biology2008
Using microarrays to study the microenvironment in tumor biology: the crucial role of statistics.
Review in Seminars in cancer biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 11 citations in OpenAlex.
- Improving the quality of biomarker discovery research: the right samples and enough of them.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2015Article
- Improving the biomarker pipeline to develop and evaluate cancer screening tests.Journal of the National Cancer Institute · 2009Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Microarrays represent a potentially powerful tool for better understanding the role of the microenvironment on tumor biology. To make the best use of microarray data and avoid incorrect or unsubstantiated conclusions, care must be taken in the statistical analysis. To illustrate the statistical issues involved we discuss three microarray studies related to the microenvironment and tumor biology involving: (i) prostatic stroma cells in cancer and non-cancer tissues; (ii) breast stroma and epithelial cells in breast cancer patients and non-cancer patients; and (iii) serum associated with wound response and stroma in cancer patients. Using these examples we critically discuss three types of analyses: differential gene expression, cluster analysis, and class prediction. We also discuss design issues.
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