DepMap-Analytics/ADAM2: Adaptive Daisy Model

The ADaM package implements a semi-supervised algorithm for computing a fuzzy-intersection of non-fuzzy sets by adaptively determining the minimal number of sets to which an element should belong in order to be a member of the fuzzy-intersection (the membership threshold). This threshold maximises the deviance from expectation of the cardinality of the resulting fuzzy-intersection, as well as the coverage of predefined elements. This method can be used to identify the minimal number of cell lines from a given tissue in which the inactivation of a gene (for example via CRISPR-Cas9 targeting) should exert a reduction of viabilty (or fitness effect) in order for that gene to be considered a core-fitness essential gene for the tissue under consideration. This method is used to discriminate between core-fitness and context-specific essential genes in a study describing a large scale genome-wide CRISPR-Cas9 pooled drop-out screening ( Behan FM & Iorio F & Picco G et al., Prioritisation of cancer therapeutic targets using CRISPR-Cas9 screens. Nature, In press).

install.packages("remotes")
remotes::install_github("DepMap-Analytics/ADAM2")