Package: corto
Type: Package
Title: Inference of Gene Regulatory Networks
Version: 1.4.0
Authors@R: c(
 person("Federico M.","Giorgi",email = "federico.giorgi@gmail.com",role=c("aut","cre")),
 person("Daniele","Mercatelli",email = "danielemercatelli@gmail.com",role="ctb"),
 person("Gonzalo","Lopez-Garcia",email = "gonzolgarcia@gmail.com",role="ctb"),
 person("Hugo","Tovar",email = "hatovar@inmegen.gob.mx",role="ctb"),
 person("Hualin","Wang",email = "wanghualin@stu.njmu.edu.cn",role="ctb"))
Maintainer: Federico M. Giorgi <federico.giorgi@gmail.com>
Description: We present 'corto' (Correlation Tool), a simple package to infer
 gene regulatory networks and visualize master regulators from gene expression
 data using DPI (Data Processing Inequality) and bootstrapping to recover edges.
 An initial step is performed to calculate all significant
 edges between a list of source nodes (centroids) and target genes.
 Then a DPI step removes edges: by default, for each target only the edge
 from the centroid with the strongest correlation is kept; optionally, the
 ARACNe rule removes an edge only if it is the weakest in a triplet of two
 centroids and one target. A bootstrapping process then calculates
 the robustness of the network, eventually re-adding edges previously removed by DPI.
 The algorithm has been optimized to run outside a computing cluster, using a fast correlation
 implementation. The package finally provides functions to calculate network enrichment
 analysis from RNA-Seq and ATAC-Seq signatures as described in the article by
 Giorgi lab (2020) <doi:10.1093/bioinformatics/btaa223>.
License: LGPL-3
Encoding: UTF-8
Depends: R (>= 3.6)
NeedsCompilation: no
Imports: grDevices, graphics, methods, parallel, pbapply, plotrix,
        stats, utils
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Config/roxygen2/version: 8.1.0
Packaged: 2026-10-20 18:31:24 UTC; feder
Author: Federico M. Giorgi [aut, cre],
  Daniele Mercatelli [ctb],
  Gonzalo Lopez-Garcia [ctb],
  Hugo Tovar [ctb],
  Hualin Wang [ctb]
Repository: CRAN
Date/Publication: 2026-10-21 13:20:23 UTC
