Tools to make it easy to work with microtiter plate-shaped data
Latest commit bb310ed Jan 29, 2017 @seaaan seaaan Remove blog post
Failed to load latest commit information.
R use seq_len instead of 1:length Oct 4, 2016
inst Add CITATION file for citation() function with link to JOSS paper Nov 10, 2016
man Rename package to plater Oct 4, 2016
tests Rename package to plater Oct 4, 2016
vignettes Remove "vignette title" from vignette index entry line of vignette. Oct 5, 2016
.gitignore Commit project file. Oct 4, 2016
.travis.yml Put back sudo: required in travis Sep 25, 2016 Add code of conduct and rearrange README for rOpenSci Jul 25, 2016
DESCRIPTION version bump after cran acceptance Oct 6, 2016
LICENSE Add JOSS files Jul 25, 2016
NAMESPACE Rename package to plater Oct 4, 2016 Update date Oct 5, 2016
README.Rmd Add zenodo DOI Oct 27, 2016 Add zenodo DOI Oct 27, 2016 Change title Oct 6, 2016
paper.bib Add JOSS files Jul 25, 2016 Change title Oct 6, 2016
plater.Rproj Commit project file. Oct 4, 2016


Travis-CI Build Status CRAN version CRAN downloads DOI

plater makes it easy to work with data from experiments performed in plates. It is aimed at scientists and analysts who deal with microtiter plate-based instruments.


plater is available through CRAN. Just run:


Getting your data in

Many scientific instruments (such as plate readers and qPCR machines) produce data in tabular form that mimics a microtiter plate: each cell corresponds to a well as physically laid out on the plate. For experiments like this, it's often easiest to keep records of what was what (control vs. treatment, concentration, sample type, etc.) in a similar plate layout form.

But data in those dimensions aren't ideal for analysis. That's where read_plate() and add_plate() come in.

  • read_plate() takes data in plate layout form and converts it to a data frame, with one well per row, identified by well name.
  • add_plate() does the same thing, but merges the new columns into an existing data frame you provide.

In other words, these functions seamlessly convert plate-shaped data (easy to think about) into tidy data (easy to analyze).

To make it even easier, if you have multiple plates in an experiment, use read_plates() to read them all in and combine them into a single data frame.

Seeing your data

Sometimes it's useful to map your data back onto a plate (are the weird outliers all from the same corner of the plate?). For that, there's view_plate(), which takes a data frame with one well per row, and lays it out like it's on a plate.


For a detailed example of how to use plater, check out the vignette.

Code of conduct

plater is developed under a Contributor Code of Conduct. To contribute to its development, you must agree to abide by its terms.

ropensci footer