Package: simphony 1.0.3

Jake Hughey

simphony: Simulating Large-Scale, Rhythmic Data

A tool for simulating rhythmic data: transcriptome data using Gaussian or negative binomial distributions, and behavioral activity data using Bernoulli or Poisson distributions. See Singer et al. (2019) <doi:10.7717/peerj.6985>.

Authors:Jake Hughey [aut, cre], Jordan Singer [aut], Darwin Fu [ctb]

simphony_1.0.3.tar.gz
simphony_1.0.3.zip(r-4.7)simphony_1.0.3.zip(r-4.6)simphony_1.0.3.zip(r-4.5)
simphony_1.0.3.tgz(r-4.6-any)simphony_1.0.3.tgz(r-4.5-any)
simphony_1.0.3.tar.gz(r-4.7-any)simphony_1.0.3.tar.gz(r-4.6-any)
simphony_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
simphony/json (API)

# Install 'simphony' in R:
install.packages('simphony', repos = c('https://hugheylab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hugheylab/simphony/issues

Pkgdown/docs site:https://simphony.hugheylab.org

Datasets:
  • defaultDispFunc - Default function for mapping expected counts to dispersion.

On CRAN:

Conda:

rhythmic-datasimphony

4.78 score 3 stars 2 scripts 242 downloads 5 exports 4 dependencies

Last updated from:f5a705e50e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK121
source / vignettesOK251
linux-release-x86_64OK121
macos-release-arm64OK104
macos-oldrel-arm64OK82
windows-develOK92
windows-releaseOK69
windows-oldrelOK65
wasm-releaseOK124

Exports:getExpectedAbundgetSampledAbundmergeSimDatasimphonysplitDiffFeatureGroups

Dependencies:codetoolsdata.tableforeachiterators

Using simphony to evaluate rhythm detection
Load the packages we'll use | Simulate the data | Plot the simulated time-course for selected genes | Detect rhythmic genes | Evaluate accuracy of rhythmic gene detection
Rendered fromintroduction.Rmdusingknitr::rmarkdown

Last update: 2022-04-11
Started: 2018-10-26

Using simphony's various options
Load required packages | Evenly-spaced timepoints | Custom rhythm function | Specified timepoints | Random timepoints | Time-dependent amplitude and base | Differential rhythmicity between conditions | Controlling negative binomial dispersion and base | Poisson sampling at high resolution
Rendered fromexamples.Rmdusingknitr::rmarkdown

Last update: 2022-04-11
Started: 2019-03-08