Crandore Hub

SIGN

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.

README

Overview
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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.)


Installation
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``` r
# Install from CRAN
install.packages('SIGN')

# Installing the development version from GitHub:
# install.packages("devtools")
devtools::install_github("bhklab/SIGN")

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 SIGN_0.1.0.tar.gz 12.2 KiB
0.1.0 rolling linux/noble R-4.5 SIGN_0.1.0.tar.gz 12.2 KiB
0.1.0 rolling source/ R- SIGN_0.1.0.tar.gz 12.2 KiB
0.1.0 latest linux/jammy R-4.5 SIGN_0.1.0.tar.gz 12.2 KiB
0.1.0 latest linux/noble R-4.5 SIGN_0.1.0.tar.gz 12.2 KiB
0.1.0 latest source/ R- SIGN_0.1.0.tar.gz 12.2 KiB
0.1.0 2026-04-26 source/ R- SIGN_0.1.0.tar.gz 12.2 KiB
0.1.0 2026-04-23 source/ R- SIGN_0.1.0.tar.gz 12.2 KiB
0.1.0 2025-04-20 source/ R- SIGN_0.1.0.tar.gz 12.2 KiB

Dependencies (latest)

Imports