seqwrap 0.7.0

• Updated documentation for CRAN submission.

seqwrap 0.6.3

• CRAN-readiness pass:
  • Title case in DESCRIPTION (“Item-by-Item”).
  • Bumped Depends: R (>= 4.1) to reflect use of the native pipe in vignettes.
  • Replaced a non-canonical CRAN URL in the main vignette.
  • Added @return documentation to seqwrap_summarise(), simcounts(), seqwrapResults, and swcontainer.
  • Marked internal helpers (seqwrap_check, fit_fun, fit_fun_lme, data_helper, seqwrap_mtf) with @noRd so they no longer generate user-facing Rd pages.
  • Replaced seqwrap:::simcounts with seqwrap::simcounts in tests.
  • Fixed handling of cores = "max" and cores = NULL in seqwrap(); invalid values now error early.
  • Vignettes gracefully skip evaluation when optional Suggests packages (including Bioconductor edgeR) are unavailable.
  • Minor typo and roxygen-tag fixes.
• Removed the Pillon data set (moved to trainome/seqwrappaper)

seqwrap 0.6.2

• Bugs
  • Fixed a bug in printing seqwrap_results where the variable k was not declared in the function environment.
  • Fixed SUGGEST dependencies for Vignette build.

seqwrap 0.6.1

• Updated the README

seqwrap 0.6.0

• Bugs
  • Internal fix, passing “library(broom.mixed)” to clusterEvalQ is not recommended. Changed to requireNamespace(“seqwrap”).
  • Internal fix, removed triple colon on exported functions in vignette.
  • Removed getwd() in saving model output on disk (seqwrap_mtf.R).
  • Updated @importFrom stats in simcounts2.R

seqwrap 0.5.0

News

• Bugfixes

seqwrap 0.4.0

News

• Added support for nlme::lme and nlme::gls, see the vignette for the use of additional_vars when working with nlme::gls
• targetdata now supports a list of data frames. Target-specific data frames are made available by their column names.

seqwrap 0.2.0

This update has focused on improving the workflow of using seqwrap. A new function (seqwrap_compose) allows for the user to collect all data needed to iterate over targets to fit models. seqwrap can still be specified using the same arguments, but can also use a swcontainer created with seqwrap_compose. In seqwrap we only need to specify e.g. the number of cores and return/save models.

Breaking changes

• The fittin_fun argument in seqwrap has been replaced by modelfun.

New features

• seqwrap_compose let’s you collect all data elements and arguments needed to run iterative modelling with seqwrap without initializing it.

• seqwrap:::simcounts was created as an internal function used in testing. It creates a simulated data set of counts based on variation across genes in a set of parameters.

• A new set of classes and methods has been written using the S7 OOP system. This means that data is validated to prevent errors in setting up the models and data.

• targetdata is now available as an argument in seqwrap and seqwrap_compose making it possible to supply target-wise values used in the arguments. E.g. setting the dispersion parameter to a fixed value.

• Using a swcontainer object as the first argument in seqwrap followed by a named argument will lead to an update of the swcontainer object before any modelling.

• seqwrap_summarise efficiently combine data frames from summary and evaluation functions.

• and more…

Known limitations