Title:	Read, Tidy, and Display Data from Microtiter Plates
Version:	1.0.5
Description:	Tools for interacting with data from experiments done in microtiter plates. Easily read in plate-shaped data and convert it to tidy format, combine plate-shaped data with tidy data, and view tidy data in plate shape.
Depends:	R (≥ 3.1.0)
Imports:	utils, dplyr (> 0.4.3), rlang
Suggests:	testthat, knitr, rmarkdown
License:	GPL-3
URL:	https://docs.ropensci.org/plater/, https://github.com/ropensci/plater
BugReports:	https://github.com/ropensci/plater/issues
VignetteBuilder:	knitr
RoxygenNote:	7.3.2
Encoding:	UTF-8
NeedsCompilation:	no
Packaged:	2024-10-25 18:59:18 UTC; smhughes
Author:	Sean Hughes [aut, cre]
Maintainer:	Sean Hughes <smhughes@uw.edu>
Repository:	CRAN
Date/Publication:	2024-10-25 20:10:01 UTC

plater: Read, Tidy, and Display Data from Microtiter Plates

Description

Tools for interacting with data from experiments done in microtiter plates. Easily read in plate-shaped data and convert it to tidy format, combine plate-shaped data with tidy data, and view tidy data in plate shape.

plater defines a simple, plate-shaped file format for data storage, so it's easy to remember the experimental design. The package provides functions to seamlessly convert between that format and a tidy data frame that's optimal for analysis. check_plater_format is provided to help you manage plate-shaped files.

You can work with purely plate-shaped data (read_plate and read_plates), as well as with a combination of plate-shaped data and tidy data (add_plate). It further allows easy plate-shaped visualization of tidy data (view_plate).

Author(s)

Maintainer: Sean Hughes smhughes@uw.edu (ORCID)

See Also

Useful links:

• https://docs.ropensci.org/plater/

• https://github.com/ropensci/plater

• Report bugs at https://github.com/ropensci/plater/issues

Useful links:

• https://docs.ropensci.org/plater/

• https://github.com/ropensci/plater

• Report bugs at https://github.com/ropensci/plater/issues

Read a plater-formatted file and combine it with an existing data frame.

Description

Converts data from plater format to a data frame with one well per row and merges it into an existing data frame by well name.

Usage

add_plate(data, file, well_ids_column, sep = ",")

Arguments

Details

If data contains more wells than in file, NA will be added to the merged column(s) for those wells. If the file contains more wells than data, those wells will be added to the bottom of the result with NA for the columns in data.

Value

Returns data as a tibble with as many new columns as plates in file. Empty wells are indicated with NA.

Examples

# Part of the data is tidy
file <- system.file("extdata", "example-2-part-A.csv", package = "plater")
data <- read.csv(file)

# Part of the data is plate-shaped
plate_shaped <- system.file("extdata", "example-2-part-B.csv", package = "plater")

# Combine the two
data <- add_plate(
   data = data, 
   file = plate_shaped,
   well_ids_column = "Wells")

# Now data are tidy
head(data)

Check whether a file is in plater format.

Description

Runs the provided file through a number of diagnostics to determine whether it is a valid plater format file and displays information about any deficiencies found.

Usage

check_plater_format(file, sep = ",")

Arguments

Value

Displays a number of messages as it checks the file. Will stop with a descriptive error message if the file is not formatted correctly.

Examples

file_path <- system.file("extdata", "example-1.csv", package = "plater")

data <- check_plater_format(file_path)

Read a plater-formatted file and turn it into a tidy data frame.

Description

Converts data from plater format to a data frame with one well per row identified by well name.

Usage

read_plate(file, well_ids_column = "Wells", sep = ",")

Arguments

Value

Returns a data frame with each well as a row. One column will be named with well_ids_column and contain the well names (A01, A02..). There will be as many additional columns as layouts in file. Empty wells are omitted.

plater format

The .csv file should be formatted as a microtiter plate. The top-left most cell contains the name to use for the column representing that plate. For example, for a 96-well plate, the subsequent wells in the top row should be labeled 1-12. The subsequent cells in the first column should be labeled A-H. That is:

In this example, the cells within the plate contain the well IDs ("A01", "A02"), but they may contain arbitrary characters: numbers, letters, or punctuation. Any cell may also be blank.

Note that Microsoft Excel will sometimes include cells that appear to be blank in the .csv files it produces, so the files may have spurious columns or rows outside of the plate, causing errors. To solve this problem, copy and paste just the cells within the plate to a fresh worksheet and save it.

Multiple columns

Multiple columns of information about a plate can be included in a single file. After the first plate, leave one row blank, and then add another plate formatted as described above. (The "blank" row should appear as blank in a spreadsheet editor, but as a row of commas when viewed as plain text.) As many plates as necessary can be included in a single file (e.g. data measured, subject, treatment, replicate, etc.).

Examples

file_path <- system.file("extdata", "example-1.csv", package = "plater")

# Data are stored in plate-shaped form
data <- read_plate(
   file = file_path,
   well_ids_column = "Wells")

# Now data are tidy
head(data)

Read multiple plater-formatted files and combine result into one data frame.

Description

A wrapper around read_plate that handles multiple plates and combines them all into a single data frame.

Usage

read_plates(files, plate_names = NULL, well_ids_column = "Wells", sep = ",")

Arguments

Value

Returns a data frame like that returned by read_plate, containing the data from all of the plates. The plates will be identified with a column called "Plate" containing the names given in plate_names.

Examples

# Combine multiple files into one tidy data frame
file1 <- system.file("extdata", "example-1.csv", package = "plater")
file2 <- system.file("extdata", "more-bacteria.csv", package = "plater")

# Data are stored in plate-shaped form
data <- read_plates(
   files = c(file1, file2),
   plate_names = c("Experiment 1", "Experiment 2"),
   well_ids_column = "Wells")

# Data from both plates are tidy and in the same data frame
head(data)

Displays the data in the form of a microtiter plate.

Description

Displays the data in the form of a microtiter plate.

Usage

view_plate(data, well_ids_column, columns_to_display, plate_size = 96)

Arguments

Value

A depiction of the data in columns_to_display as though laid out on a microtiter plate with plate_size wells.

Examples

# Generate some tidy data
data <- data.frame(Wells = paste0(LETTERS[1:3], 0, rep(1:4, each = 3)), 
Species = rep(c("Alien", "Human", "Cat"), 4), 
OxygenProduction = round(rnorm(12), 3))
head(data)

# See which wells had cells from which species and the amount of oxygen 
# produced for each well
view_plate(data, "Wells", c("Species", "OxygenProduction"), 12)