Models high-dimensional data, such as RNA-seq or proteomic data using an item-by-item strategy. The package contains functions to wrap high-dimensional data and iterate over them using established R packages for regression modelling (e.g., 'glmmTMB' or 'mgcv').
The seqwrap R package allows you to model high-dimensional data using
an item-by-item strategy with a specific model engine. Using seqwrap,
you can fit, e.g., gene/transcript data from an RNA sequencing
experiment to a model specified with random effects or custom
distributions. This is possible because seqwrap efficiently iterates
over all items (e.g., genes) and fits the data to the same model
formulation using established R packages for regression modeling.
See the package Vignettes for examples.
Install the released version of seqwrap from CRAN:
install.packages("seqwrap")
Or install the development version from GitHub:
# install.packages("pak")
pak::pkg_install("trainome/seqwrap")