XcisClique: A Tool for Analyzing Regulatory Bicliques in Arabidopsis
Author Information
Author(s): Pati Amrita, Vasquez-Robinet Cecilia, Heath Lenwood S, Grene Ruth, Murali TM
Primary Institution: Virginia Polytechnic Institute and State University
Hypothesis
Can the XcisClique system effectively identify regulatory bicliques in Arabidopsis thaliana using genomic and gene expression data?
Conclusion
XcisClique successfully identifies statistically significant regulatory bicliques that may indicate the involvement of sets of genes in biological functions.
Supporting Evidence
- XcisClique identifies new motif and gene combinations that might indicate as yet unidentified involvement of sets of genes in biological functions.
- The system integrates genomic and gene expression data to identify statistically significant regulatory bicliques.
- Statistical significance is assessed using a combination of hypergeometric distribution and Spearman correlation coefficients.
Takeaway
XcisClique is a computer program that helps scientists find groups of genes that work together by looking at their DNA and how they behave in different situations.
Methodology
XcisClique uses a bipartite graph to model gene and motif interactions, applying the Apriori algorithm to identify maximal bicliques and assess their statistical significance using hypergeometric distribution.
Limitations
The system relies on known motifs and does not include motif discovery, which may limit its applicability to organisms with less documented regulatory motifs.
Participant Demographics
The study focuses on Arabidopsis thaliana, a model organism in plant biology.
Statistical Information
P-Value
3.955 × 10^-3
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
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