Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 98, Issue 16, Pages 8961-8965Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.161273698
Keywords
-
Categories
Funding
- NCI NIH HHS [R33 CA088327, CA88327, R21 CA088327] Funding Source: Medline
- NHLBI NIH HHS [HL 66620] Funding Source: Medline
- Wellcome Trust Funding Source: Medline
Ask authors/readers for more resources
We introduce a general technique for making statistical inference from clustering tools applied to gene expression microarray data. The approach utilizes an analysis of variance model to achieve normalization and estimate differential expression of genes across multiple conditions. Statistical inference is based on the application of a randomization technique, bootstrapping. Bootstrapping has previously been used to obtain confidence intervals for estimates of differential expression for individual genes. Here we apply bootstrapping to assess the stability of results from a cluster analysis. We illustrate the technique with a publicly available data set and draw conclusions about the reliability of clustering results in light of variation in the data. The bootstrapping procedure relies on experimental replication. We discuss the implications of replication and good design in microarray experiments.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available