FeatureTable

Note: I still consider FeatureTable to be in the pre-release stage. The code itself is well tested and I use it in my own research, but the API has not stabalized and is still subject to breaking changes when I cut a new release.

Installing

Go to the Releases page and click on the latest release. Follow the instructions there to install. There are few strictly required dependencies, but some features will only work if you install some extras. See the dependencies section of this readme.

If you are an R developer, feel free to clone the repository and use developer tools to build and use the package.

Usage

Vignettes

FeatureTable comes with a few detailed vignettes describing its usage. After installing, you can view them with the following command:

browseVignettes("featuretable")

Function docs

Additionally, each function has a lot of info in the help section. You can run ?featuretable to get an overview of everything. Click on the links in there to get to individual function docs. You can also access function docs with the ?, e.g., ?keep_samples.

Dependencies

Required

• R6
• rlang

Suggested

• If you want nice plots, I suggest you also install ggplot2, ggrepel, and biplotr.
• If you want fancy zero replacement, you should install zCompositions.
• If you need to import or export phyloseq objects, then you need to install phyloseq.
• If you want to build the vignettes yourself, you will need knitr and rmarkdown. Also, some of the vignettes use magrittr to keep things clean.

Test suite dependencies

• If you want to run the test suite locally, then you need to install testthat.
• Some of the tests require additional packages. If you don't have them, those tests should be skipped.
  • Testing plotting functions requires vdiffr.
  • If you want to run the coverage report for yourself, then you will need to install covr.
  • Some of the tests compare bespoke implementations of certain functions to their counterparts in dplyr, tibble, and tidyr.
  • Property tests require the hedgehog package.

R v3 and v4 compatibility

• All the unit tests pass on R v3.6.3 (tested with this Docker image) and v4.0.2 (tested with this Docker image).
• Literally every time data.frame or as.data.frame is called in the FeatureTable code and tests , stringsAsFactors = TRUE is passed in as an argument.
  • So, if you need a specific stable sorting of your sringly data, you need to set the factor levels yourself.
  • In theory, you should be fine passing in data.frames that don't have their strings as factors, since FeatureTable will convert all strings to factors, but as of 2020-09-22, I haven't tested it.
  • This behavior may change in the future though!
• One thing to note is that as.data.frame.FeatureTable does not have a stringsAsFactors parameter. This shouldn't be a problem as string-esque data is not allowed in the data field anyway.