Package: seqwrap 0.7.0.9000

Daniel Hammarström

seqwrap: Item-by-Item Iterative Model Fitting

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').

Authors:Daniel Hammarström [aut, cre, cph], Chidimma Echebiri [ctb]

seqwrap_0.7.0.9000.tar.gz
seqwrap_0.7.0.9000.zip(r-4.7-any)seqwrap_0.7.0.9000.zip(r-4.6-any)seqwrap_0.7.0.9000.zip(r-4.5-any)
seqwrap_0.7.0.9000.tgz(r-4.6-any)seqwrap_0.7.0.9000.tgz(r-4.5-any)
seqwrap_0.7.0.9000.tar.gz(r-4.7-any)seqwrap_0.7.0.9000.tar.gz(r-4.6-any)
seqwrap_0.7.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
seqwrap/json (API)

# Install 'seqwrap' in R:

install.packages('seqwrap', repos = c('https://trainome.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/trainome/seqwrap/issues

Datasets:

dungan_counts - Dungan et al 2022 counts

On CRAN:

quarto

6.05 score 2 stars 47 scripts 264 downloads 9 exports 105 dependencies

Last updated from:5a93c286d2. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	225
source / vignettes	OK	252
linux-release-x86_64	OK	222
macos-release-arm64	OK	330
macos-oldrel-arm64	OK	256
windows-devel	OK	226
windows-release	OK	193
windows-oldrel	OK	181
wasm-release	OK	174

Exports:generic_evaluation generic_summary seqwrap seqwrap_compose seqwrap_summarise seqwrapResults simcounts simcounts2 swcontainer

Dependencies:ape askpass backports base64enc boot broom broom.mixed bslib cachem cli coda codetools commonmark cpp11 crosstalk curl data.table DHARMa digest doParallel dplyr evaluate farver fastmap fontawesome forcats foreach fs furrr future gap gap.datasets generics ggplot2 globals glue gtable highr htmltools htmlwidgets httpuv httr isoband iterators jquerylib jsonlite knitr labeling later lattice lazyeval lifecycle listenv lme4 lmtest magrittr MASS Matrix memoise mgcv mime minqa nlme nloptr openssl otel parallelly pbapply pillar pkgconfig plotly plyr promises purrr qgam R6 rappdirs rbibutils RColorBrewer Rcpp RcppEigen Rdpack reformulas rlang rmarkdown S7 sass scales shiny sourcetools stringi stringr sys tibble tidyr tidyselect tinytex utf8 vctrs viridisLite withr xfun xtable yaml zoo

Fitting models with seqwrap

References

Rendered fromfitting-models-with-seqwrap.html.asisusingR.rsp::asis

Last update: 2026-05-13
Started: 2026-05-13

Working with lme4 and nlme in seqwrap

Fitting count data to a negative binomial model using glmmTBM | Fitting transformed count data to a Gaussian model using lme4 | Using nlme::lme and nlme::gls, need for additional_vars

Rendered fromfitting-lme4-nlme-models-with-seqwrap.qmdusingquarto::html

Last update: 2026-05-13
Started: 2026-04-08

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Dungan et al 2022 counts	dungan_counts
Generic evaluation for model fits	generic_evaluation
Generic summaries for model parameter estimates.	generic_summary
Print method for objects of class seqwrapResults	print.seqwrapResults
A flexible upper-level wrapper for iterative modelling using any available fitting algorithm	seqwrap
Compose a swcontainer object for use in the seqwrap function.	seqwrap_compose
Summarise seqwrapResults objects	seqwrap_summarise
seqwrapResults class	seqwrapResults
Simulate counts from a simple experiment (paired or unpaired) using Poisson or negative binomial distributions.	simcounts
Simulate counts from a parallel groups design with three time-points	simcounts2
seqwrap container class	swcontainer