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iSEEtree

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The goal of iSEEtree is to provide panels related to TreeSummarizedExperiment objects which facilitate the interactive visualisation of microbiome data in iSEE.

Installation instructions

The release version of iSEEtree can be installed from Bioconductor as follows:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("iSEEtree")

Contributors or users interested in the latest functionality can install the devel version of iSEEtree as follows:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("iSEEtree")

Example

The basic functionality of iSEEtree can be explored as follows:

library(iSEEtree)
library(mia)
library(scater)

# Import TreeSE
data("Tengeler2020", package = "mia")
tse <- Tengeler2020

# Add relabundance assay
tse <- transformAssay(tse, method = "relabundance")

# Add reduced dimensions
tse <- runMDS(tse, assay.type = "relabundance")

# Launch iSEE
if (interactive()) {
  iSEE(tse)
}

Code of Conduct

Please note that the iSEEtree project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms. Contributions are welcome in the form of feedback, issues and pull requests. You can find the contributor guidelines of the miaverse here.

Acknowledgements

Please note that iSEEtree was only made possible thanks to many other R and bioinformatics software authors, which are cited either in the vignettes and/or the paper(s) describing this package. In particular, iSEEtree implements the miaViz package for microbiome data visualisation to create panels that are specific for TreeSummarizedExperiment objects. Not surprisingly, it also depends on the generic panels from iSEE.

This package was developed using the following resources:

  • usethis to generate an initial template.
  • Continuous code testing is performed on GitHub actions and include R CMD check, BiocCheck and testthat.
  • Code coverage assessment is possible thanks to codecov.
  • The documentation website is automatically updated thanks to pkgdown.
  • The documentation is formatted thanks to devtools and roxygen2.
  • All the actions above are made reproducible by rworkflows