cowplot, ggthemes, knitr, parallel, rgeos, rmarkdown,
spelling, testthat

Given a landscape resistance surface, creates minimum planar graph
(Fall et al. (2007) <doi:10.1007/s10021-007-9038-7>) and grains of connectivity
(Galpern et al. (2012) <doi:10.1111/j.1365-294X.2012.05677.x>) models that can be
used to calculate effective distances for landscape connectivity at multiple scales.
Documentation is provided by several vignettes, and a paper
(Chubaty, Galpern & Doctolero (2020) <doi:10.1111/2041-210X.13350>).
c(
person("Paul", "Galpern", email = "pgalpern@gmail.com", role = c("aut", "cph"),
comment = c(ORCID = "0000-0003-0099-3981")),
person("Sam", "Doctolero", email = "sam.doctolero@gmail.com", role = "aut"),
person("Alex M", "Chubaty", email = "alex.chubaty@gmail.com", role = c("aut", "cre"),
comment = c(ORCID = "0000-0001-7146-8135"))
)
covr, cowplot, ggthemes, knitr, parallel, rgeos, rmarkdown,
spelling, testthat
Paul Galpern [aut, cph] (<https://orcid.org/0000-0003-0099-3981>),
Sam Doctolero [aut],
Alex M Chubaty [aut, cre] (<https://orcid.org/0000-0001-7146-8135>)

Farzad Noorian, Anthony Mihirana de Silva
Implementation of Context Free Grammar and Grammatical Evolution for R

Context Free Grammar and Grammatical Evolution for R.

A native R implementation of grammatical evolution (GE). GE facilitates the discovery of programs that can achieve a desired goal. This is done by performing an evolutionary optimisation over a population of R expressions generated via a user-defined context-free grammar (CFG) and cost function.

A native R implementation of grammatical evolution (GE).
GE facilitates the discovery of programs that can achieve a desired goal.
This is done by performing an evolutionary optimisation over a population
of R expressions generated via a user-defined context-free grammar (CFG)
and cost function.

Comprehensive Analysis of Nucleotide Conversion Sequencing Data
c(
person("Florian", "Erhard", email = "Florian.Erhard@uni-wuerzburg.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3574-6983")),
person("Teresa", "Rummel", email = "Teresa.Rummel@uni-wuerzburg.de", role = "ctb"),
person("Lygeri", "Sakellaridi", email = "Lygeri.Sakellaridi@uni-wuerzburg.de", role = "ctb")
)
Nucleotide conversion sequencing experiments have been
developed to add a temporal dimension to RNA-seq and single-cell RNA-seq. Such
experiments require specialized tools for primary processing such as GRAND-SLAM,
(see 'Jürges et al' <doi:10.1093/bioinformatics/bty256>) and specialized tools for
downstream analyses. 'grandR' provides a comprehensive toolbox for quality control,
kinetic modeling, differential gene expression analysis and visualization of such data.
Florian Erhard [aut, cre] (<https://orcid.org/0000-0002-3574-6983>),
Teresa Rummel [ctb],
Lygeri Sakellaridi [ctb]
stats, Matrix, ggplot2, grDevices, patchwork, plyr, parallel,
reshape2, MASS, cowplot, minpack.lm, lfc, methods, utils,
numDeriv
knitr, rmarkdown, circlize, Seurat, ComplexHeatmap, ggrepel,
RCurl, DESeq2, clusterProfiler, msigdbr, fgsea, rclipboard,
cubature, lamW, DT, RColorBrewer, eulerr, gsl, htmltools,
labeling, matrixStats, monocle, VGAM, quantreg, rlang,
graphics, scales, shiny