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 all triplets containing two centroids and one target are tested
in a DPI step which removes edges. 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>.

dplyr, gplots, knitr, parallel, pbapply, plotrix, rmarkdown,
stats, utils

dplyr, gplots, knitr, methods, parallel, pbapply, plotrix,
rmarkdown, stats, utils

person(given = "James",
family = "Conigrave",
role = c("aut", "cre"),
email = "james.conigrave@gmail.com",
comment = c(ORCID = "0000-0002-8816-6229"))
Create correlation (or partial correlation) matrices. Correlation matrices are formatted with significance stars based on user preferences. Matrices of coefficients, p-values, and number of pairwise observations are returned. Send resultant formatted matrices to the clipboard to be pasted into excel and other programs. A plot method allows users to visualize correlation matrices created with 'corx'.
ppcor, crayon, ggcorrplot, glue, psych, clipr, tidyselect,
moments
James Conigrave [aut, cre] (<https://orcid.org/0000-0002-8816-6229>)

ppcor, crayon, ggcorrplot, glue, psych, clipr, tidyselect,
moments, ggpubr, ggplot2, magrittr, stats

crayon, ggcorrplot, glue, clipr, tidyselect, moments, ggpubr,
ggplot2, stats, methods, ppcor

person("Metin", family = "Bulus", role = c("aut", "cre", "cph"), email = "bulusmetin@gmail.com")
Implements generalized constrained optimal sample allocation framework for multilevel regression discontinuity studies and multilevel randomized trials with continuous outcomes. Bulus, M. (2017). Design Considerations in Three-level Regression Discontinuity Studies (Doctoral dissertation). University of Missouri, Columbia, MO.