Type: Package
Title: Learning Causal or Non-Causal Graphical Models Using Information
        Theory
Version: 1.4.2
Date: 2020-07-27
Package: miic
Description: We report an information-theoretic method which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables, commonly found in many datasets. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. This approach can be applied on a wide range of datasets and provide new biological insights on regulatory networks from single cell expression data, genomic alterations during tumor development and co-evolving residues in protein structures. For more information you can refer to: Cabeli et al. PLoS Comp. Bio. 2020 <doi:10.1371/journal.pcbi.1007866>, Verny et al. PLoS Comp. Bio. 2017 <doi:10.1371/journal.pcbi.1005662>.
Authors@R: c(
           person("Vincent", "Cabeli", role = c("aut", "cre"), email="vincent.cabeli@curie.fr"),
           person("Honghao", "Li", role = "aut", email="honghao.li@curie.fr"),
           person("Marcel", "Ribeiro Dantas", role = "aut", email = "marcel.ribeiro-dantas@curie.fr"),
           person("Nadir", "Sella", role = "aut", email = "nadir.sella@curie.fr"),
           person("Louis", "Verny",role = "aut"),
           person("Severine", "Affeldt", role = "aut"),
           person("Hervé", "Isambert", role = c("aut"), email = "Herve.Isambert@curie.fr"))
Maintainer: Vincent Cabeli <vincent.cabeli@curie.fr>
Imports: igraph, ppcor, scales, stats, Rcpp
Suggests: ggplot2 (>= 3.3.0), gridExtra
License: GPL (>= 2)
NeedsCompilation: yes
Encoding: UTF-8
SystemRequirements: C++14
LazyData: true
RoxygenNote: 7.1.1
LinkingTo: Rcpp
Author: Vincent Cabeli [aut, cre],
  Honghao Li [aut],
  Marcel Ribeiro Dantas [aut],
  Nadir Sella [aut],
  Louis Verny [aut],
  Severine Affeldt [aut],
  Hervé Isambert [aut]
Packaged: 2020-07-28 10:23:54 UTC; vcabeli
Repository: CRAN
Date/Publication: 2020-07-31 08:50:05 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-02 23:46:05 UTC; windows
Archs: i386, x64
