Journal
DNA RESEARCH
Volume 15, Issue 6, Pages 367-374Publisher
OXFORD UNIV PRESS
DOI: 10.1093/dnares/dsn025
Keywords
singular value decomposition; gene expression; gene correlation; Arabidopsis
Categories
Funding
- MEXT
- BIRD, Japan Science and Technology Agency
Ask authors/readers for more resources
Gene co-expression analysis has been widely used in recent years for predicting unknown gene function and its regulatory mechanisms. The predictive accuracy depends on the quality and the diversity of data set used. In this report, we applied singular value decomposition (SVD) to array experiments in public databases to find that co-expression linkage could be estimated by a much smaller number of array data. Correlations of co-expressed gene were assessed using two regulatory mechanisms (feedback loop of the fundamental circadian clock and a global transcription factor Myb28), as well as metabolic pathways in the AraCyc database. Our conclusion is that a smaller number of informative arrays across tissues can suffice to reproduce comparable results with a state-of-the-art co-expression software tool. In our SVD analysis on Arabidopsis data set, array experiments that contributed most as the principal components included stamen development, germinating seed and stress responses on leaf.
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