CAusal Modeling with Expression Linkage for cOmplex Traits (Camelot) provides
a framework to both model complex traits and identify the potential underlying
causal factors. Briefly, Camelot takes genotype, gene expression and phentoype
data as input, and output a linear regression model that uses genotype and expression
to predict phenotype. Powered by regularized linear regression, Camelot aims to
choose features (either genotype or gene expression) that are predictive (and likely
causal) to the phenotype. In addition, Camelot also provides functions to prioritize
genes residing within a locus that is associated with the trait.
When using Camelot, please cite the following article:
Chen BJ., Causton H.C., Mancenido D., Goddard N.L., Perlstein E.O., Pe'er D.
Harnessing gene expression to identify the genetic basis of drug resistance.
Mol Syst Biol. 2009;5:310. Epub 2009 Oct 13.
You can download the matlab functions here.
You can read detailed usage instructions here.
For any questions, please contact firstname.lastname@example.org.