Global analysis of microarray data reveals intrinsic properties in gene expression and tissue selectivity

Motivation: It is expected that individual genes have intrinsically different variability in the global expressional trend among them. Thus, the consideration of gene-specific expressional properties will help us to distinguish target-selective gene expression over non-selective over-expression. Res...

Full description

Saved in:
Bibliographic Details
Published in:Bioinformatics 2010-07, Vol.26 (14), p.1723-1730
Main Authors: Kim, Changsik, Choi, Jiwon, Park, Hyunjin, Park, Yunsun, Park, Jungsun, Park, Taesung, Cho, Kwanghui, Yang, Young, Yoon, Sukjoon
Format: Article
Language:English
Subjects:
Biological and medical sciences
Breast Neoplasms - genetics
Databases, Genetic
Female
Fundamental and applied biological sciences. Psychology
Gene Expression
Gene Expression Profiling - methods
General aspects
Genomics - methods
Humans
Internet
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Oligonucleotide Array Sequence Analysis - methods
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Motivation: It is expected that individual genes have intrinsically different variability in the global expressional trend among them. Thus, the consideration of gene-specific expressional properties will help us to distinguish target-selective gene expression over non-selective over-expression. Results: The re-standardization and integration of heterogeneous microarray datasets, available from public databases, have enabled us to determine the global expression properties of individual genes across a wide variety of experimental conditions and samples. The global averages and SDs of expression for each gene in the integrated microarray datasets were found to be intrinsic properties, which were consistent among independent collections of datasets using different microarray platforms. Using the gene-specific intrinsic parameters to rescale the microarray data, we were able to distinguish novel selective gene expression [cartilage oligomeric matrix protein (COMP) and Collagen X] in breast cancer tissues from non-selective over-expression, a difference that has not been detectable by conventional methods. Availability and Implementation: The web-based tool for GS-LAGE is available at http://lage.sookmyung.ac.kr Contact: yoonsj@sookmyung.ac.kr Supplementary information: Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btq279