Similarity Identification in Gene Expression

Provides a classification framework to use expression patterns of pathways as features to identify similarity between biological samples. It provides a new measure for quantifying similarity between expression patterns of pathways.


SIGN fasciliotates classification and clustering of biological samples relyign on expression pattersn of biological pathways. A new measure of pathway expression pattern similarity (TSC) was introduced in the package. The package has been developed and tested for RNA-seq profiles of the cells. However, it can be used for other sequencig profiles with continuous values for each feature (gene, protein, cis-regulatory elements, etc.)


# Installing the development version from GitHub:
# install.packages("devtools")


Reference manual

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0.1.0 by Benjamin Haibe-Kains, a year ago

Browse source code at

Authors: Seyed Ali Madani Tonekaboni [aut] , Gangesh Beri [aut] , Janosch Ortmann [aut] , Benjamin Haibe-Kains [aut, cre]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports stats, utils, survcomp, survival, GSVA

See at CRAN