Description: The 'DImodels' package is suitable for analysing data from biodiversity and ecosystem function studies using the Diversity-Interactions (DI) modelling approach introduced by Kirwan et al. (2009) <doi:10.1890/08-1684.1>. Suitable data will contain proportions for each species and a community-level response variable, and may also include additional factors, such as blocks or treatments. The package can perform data manipulation tasks, such as computing pairwise interactions (the DI_data() function), can perform an automated model selection process (the autoDI() function) and has the flexibility to fit a wide range of user-defined DI models (the DI() function).

Authors@R: c(person("Rafael", "de Andrade Moral", role = c("aut", "cre"), email = "rafael.deandrademoral@mu.ie"), person("John", "Connolly", role = "aut"), person("Rishabh", "Vishwakarma", role = "ctb"), person("Caroline", "Brophy", role = "aut"))
Imports: methods, graphics, stats, utils, hnp, rootSolve, multcomp
Suggests: ggplot2, knitr, rmarkdown, markdown

Title: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell
Description: An open, multi-algorithmic pipeline for easy, fast and efficient
analysis of cellular sub-populations and the molecular signatures that
characterize them. The pipeline consists of four successive steps: data
pre-processing, cellular clustering with pseudo-temporal ordering, defining
differential expressed genes and biomarker identification. This package
implements extensions of the work published by Ghannoum et. al. (2019)
Imports: methods, TSCAN, boot, httr, mclust, statmod, igraph, RWeka,
philentropy, NetIndices, png, grDevices, readr, RColorBrewer,
ggplot2, rpart, fpc, cluster, rpart.plot, tsne, AnnotationDbi,
org.Hs.eg.db, graphics, stats, utils, impute
Depends: R (>= 4.0), SingleCellExperiment

differential expressed genes and biomarker identification. More details on
Ghannoum et. al. (2021) <doi:10.3390/ijms22031399>. This package implements
extensions of the work published by Ghannoum et. al. (2019)
philentropy, NetIndices, png, grDevices, RColorBrewer, ggplot2,
rpart, fpc, cluster, rpart.plot, tsne, AnnotationDbi,