A statistical perspective on gene expression data analysis Journal Article
| Authors: | Satagopan, J. M.; Panageas, K. S. |
| Article Title: | A statistical perspective on gene expression data analysis |
| Abstract: | Rapid advances in biotechnology have resulted in an increasing interest in the use of oligonucleotide and spotted cDNA gene expression microarrays for medical research. These arrays are being widely used to understand the underlying genetic structure of various diseases, with the ultimate goal to provide better diagnosis, prevention and cure. This technology allows for measurement of expression levels from several thousands of genes simultaneously, thus resulting in an enormous amount of data. The role of the statistician is critical to the successful design of gene expression studies, and the analysis and interpretation of the resulting voluminous data. This paper discusses hypotheses common to gene expression studies, and describes some of the statistical methods suitable for addressing these hypotheses. S-plus and SAS codes to perform the statistical methods are provided. Gene expression data from an unpublished oncologic study is used to illustrate these methods. Copyright © 2003 John Wiley & Sons, Ltd. |
| Keywords: | clinical article; controlled study; treatment outcome; review; cluster analysis; classification; genetic variability; biotechnology; gene expression regulation; cancer genetics; statistical analysis; data interpretation, statistical; diagnostic value; oligonucleotide array sequence analysis; medical research; expressed sequence tag; gene identification; dna, neoplasm; data analysis; genomics; dna microarray; software; oligonucleotide; mathematical computing; biostatistics; analytical error; complementary dna; hypothesis; preventive medicine; factor analysis, statistical; class prediction; class discovery; gene expression system; humans; human; compound covariate predictor; fisher's linear discriminant function; hierarchial clustering; multiple correction |
| Journal Title: | Statistics in Medicine |
| Volume: | 22 |
| Issue: | 3 |
| ISSN: | 0277-6715 |
| Publisher: | John Wiley & Sons |
| Date Published: | 2003-02-15 |
| Start Page: | 481 |
| End Page: | 499 |
| Language: | English |
| DOI: | 10.1002/sim.1350 |
| PUBMED: | 12529876 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Export Date: 25 September 2014 -- Source: Scopus |
Altmetric
Citation Impact
BMJ Impact Analytics
Related MSK Work