Systematic Identification of Bimodally Expressed Genes Using
RNAseq Data
Provides models to identify bimodally expressed genes from
RNAseq data based on the Bimodality Index. SIBERG models the  RNAseq data in
the finite mixture modeling framework and incorporates mechanisms  for
dealing with RNAseq normalization. Three types of mixture models are
implemented,  namely, the mixture of log normal, negative binomial, or
generalized poisson distribution. See Tong et al. (2013)
<doi:10.1093/bioinformatics/bts713>.

Provides models to identify bimodally expressed genes from
RNAseq data based on the Bimodality Index. SIBERG models the  RNAseq data in
the finite mixture modeling framework and incorporates mechanisms  for
dealing with RNAseq normalization. Three types of mixture models are
implemented,  namely, the mixture of log normal, negative binomial, or
generalized Poisson distribution. See Tong et al. (2013)
<doi:10.1093/bioinformatics/bts713>.

The code computes the structural intervention distance (SID) between a true directed acyclic graph (DAG) and an estimated DAG. Definition and details about the implementation can be found in J. Peters and P. Bühlmann: "Structural intervention distance (SID) for evaluating causal graphs", Neural Computation 27, pages 771-799, 2015.

Subgroup Identification Based on Differential Effect Search
Provides function to apply "Subgroup Identification based on Differential Effect Search" (SIDES) method proposed by Lipkovich et al. (2011) <doi:10.1002/sim.4289>.

Similarity Identification in Gene Expression
c(
person("Seyed Ali", "Madani Tonekaboni", , email = "ali.madanitonekaboni@mail.utoronto.ca", role = c("aut")),
person("Gangesh", "Beri", , email = "gangesh.beri@uhnresearch.ca", role = c("aut")),
person("Janosch", "Ortmann", , email = "janosch.ortmann@gmail.com", role = c("aut")),
person("Benjamin", "Haibe-Kains", , email = "benjamin.haibe.kains@utoronto.ca", role = c("aut", "cre"))
)
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.
Seyed Ali Madani Tonekaboni [aut],
Gangesh Beri [aut],
Janosch Ortmann [aut],
Benjamin Haibe-Kains [aut, cre]