Extracting binary signals from microarray time-course data.
Nucleic Acids Res
; 35(11): 3705-12, 2007.
Article
in En
| MEDLINE
| ID: mdl-17517782
ABSTRACT
This article presents a new method for analyzing microarray time courses by identifying genes that undergo abrupt transitions in expression level, and the time at which the transitions occur. The algorithm matches the sequence of expression levels for each gene against temporal patterns having one or two transitions between two expression levels. The algorithm reports a P-value for the matching pattern of each gene, and a global false discovery rate can also be computed. After matching, genes can be sorted by the direction and time of transitions. Genes can be partitioned into sets based on the direction and time of change for further analysis, such as comparison with Gene Ontology annotations or binding site motifs. The method is evaluated on simulated and actual time-course data. On microarray data for budding yeast, it is shown that the groups of genes that change in similar ways and at similar times have significant and relevant Gene Ontology annotations.
Full text:
1
Database:
MEDLINE
Main subject:
Software
/
Computational Biology
/
Oligonucleotide Array Sequence Analysis
/
Gene Expression Profiling
Type of study:
Evaluation_studies
Language:
En
Journal:
Nucleic Acids Res
Year:
2007
Type:
Article
Affiliation country:
United States