Package 'seahtrue'

Glueing mulltiple plates from a folder

Description

This function takes a folder path and on the available .xlsx files the revive_xfplate() function is run and output in one nested tibble.

Usage

glue_xfplates(folderpath_seahorse, arg_is_folder)

Arguments

folderpath_seahorse	the path to a folder where the .xlsx files are located or a vector of strings pointing to the path of each individual file
arg_is_folder	either TRUE or FALSE. When the input is a vector of path strings use FALSE, is it points to a folder use TRUE

Value

a nested tibble with all files organized in a row

Examples

c(
    system.file("extdata",
        "20191219_SciRep_PBMCs_donor_A.xlsx",
        package = "seahtrue"
    ),
    system.file("extdata",
        "20191219_SciRep_PBMCs_donor_A.xlsx",
        package = "seahtrue"
    )
) |>
    glue_xfplates(arg_is_folder = FALSE)

---

Dataset PBMC donor A

Description

A dataset containing output for the "20191219_SciRep_PBMCs_donor_A.xlsx" file. This experiment was part of the study that was published in Janssen et al. (2021) Sci rep 11:1662. This is data from PBMCs that were isolated from buffy coats as described in the material and methods section of Janssen et al. (2021). The .xlsx file is the result of a single XF experiment on one plate. This .xlsx file was used as input for the revive_xfplate() function. The output of that function contains the read, preprocessed, and validated data in the form a a nested tibble. The file '20191219_SciRep_PBMCs_donor_A.xlsx' can be found in the inst/extdata directory.

Usage

data(revive_output_donor_A)

Format

A data frame with 1 row and 7 variables.

plate_id

Barcode plate id of the well plate containing the samples

filepath_seahorse

Path, and basename to .xlsx file

date_run

Date and time when the plate was run

date_processed

Date and time this output from revive_xfplate() was generated

assay_info

Meta information from 'Assay Configuration' sheet and 'Calibration' sheet

injection_info

Dataframe with information from the 'Operation log' sheet

raw_data

Preprocessed raw dataframe from 'Raw' sheet

rate_data

Preprocessed rate data from 'Rate' sheet

validation_output

A list of all validation information, output, and rules that are used

Source

Janssen et al. 2021 Sci Rep 11:1162 <https://doi.org/10.1038/s41598-021-81217-4>

---

Running the read, preprocess and validate

Description

This function takes the Seahorse Wave .xlsx file and computes it through read, validate and preprocess

Usage

revive_xfplate(filepath_seahorse)

Arguments

filepath_seahorse

Absolute path to the Seahorse Excel file.

Value

A preprocessed seahorse dataset is returned as an output. This is a nested tibble with the following 7 columns:
* plate_id = Barcode plate id of the well plate containing the samples
* filepath_seahorse = Path, and basename to .xlsx input file
* date_run = Date and time when the plate was run
* date_processed = Date and time this output from revive_xfplate() was generated
* assay_info = Meta information from 'Assay Configuration' sheet and 'Calibration' sheet
* injection_info = Dataframe with information from the 'Operation log' sheet
* raw_data = Preprocessed raw dataframe from 'Raw' sheet
* rate_data = Preprocessed rate data from 'Rate' sheet
# validation_output = Output of the data checks. including rules

Examples

revive_xfplate(
    system.file("extdata",
        "20191219_SciRep_PBMCs_donor_A.xlsx",
        package = "seahtrue"
    )
)

---

Combine multiple revived xf plates into one plot for rate data

Description

In this plot the OCR or ECAR is plotted per group for each plate in a faceted gpgplot

Usage

sketch_assimilate_rate(my_df, param = "OCR", my_measurements = c(3, 6, 7, 12))

Arguments

my_df	a tibble generated by glue_xfplates() with for each row representing a single xf experiment
param	either "OCR" or "ECAR"
my_measurements	the measurements that needs to be in the plot. For example, c(3,6,7,12) for a typical mito stress test.

Value

a ggplot object

Examples

suppressMessages(
    c(
        system.file("extdata",
            "20191219_SciRep_PBMCs_donor_A.xlsx",
            package = "seahtrue"
        ),
        system.file("extdata",
            "20191219_SciRep_PBMCs_donor_A.xlsx",
            package = "seahtrue"
        )
    ) |>
        glue_xfplates(arg_is_folder = FALSE) |>
        sketch_assimilate_rate(
            param = "OCR",
            my_measurements = c(3, 4, 9, 12)
        )
)

---

Combine multiple revived xf plates into one plot for raw data

Description

In this plot the O2, pH, or its emission value at the very first measurement point plotted for all wells from all xfplates that are provided to the function.

Usage

sketch_assimilate_raw(my_df, param = "O2_mmHg")

Arguments

my_df	a tibble generated by glue_xfplates() with for each row representing a single xf experiment
param	either "O2_mmHg", "pH", "O2_em_corr" or "pH_em_corr

Value

a ggplot object

Examples

suppressMessages(
    c(
        system.file("extdata",
            "20191219_SciRep_PBMCs_donor_A.xlsx",
            package = "seahtrue"
        ),
        system.file("extdata",
            "20191219_SciRep_PBMCs_donor_A.xlsx",
            package = "seahtrue"
        )
    ) |>
        glue_xfplates(arg_is_folder = FALSE) |>
        sketch_assimilate_raw(param = "O2_mmHg")
)

---

Make an overview of plate layout, with colored groups

Description

A heatmap style ggplot figure with each well labeled with a color for each group

Usage

sketch_plate(xfplate, reorder_legend = FALSE)

Arguments

xfplate	This the 'raw_data' or the 'rate_data' tibble that is generated by the 'revive_xfplate()' function
reorder_legend	either 'TRUE' or 'FALSE'. When 'TRUE' the groups are ordered based on the number in the character string of the group. It also adds a "__00" after each character string to make the forcats::refactor(group, parse_number(group)) work.

Value

a ggplot object of a 96 well plate with the group layout

Examples

system.file("extdata",
    "20191219_SciRep_PBMCs_donor_A.xlsx",
    package = "seahtrue"
) |>
    revive_xfplate() |>
    purrr::pluck("raw_data", 1) |>
    sketch_plate(reorder_legend = TRUE)

---

Generate a plot for the rate data

Description

The sketch_rate() function uses the rate_data from the generated output from the revive_xfplate() function. The injection info is annotated in the plot, using the information form the injections provided in the original experiment. Several options are available to plot either ECAR/OCR or normalize the data with the values from the normalization cells in the .xlsx file.

A number of validations are performed to check whether the data can be plotted and whether the layout of the plot will not be ruined...

Usage

sketch_rate(
  xf_rate,
  param = "OCR",
  normalize = FALSE,
  normalize_unit = "10000 cells",
  take_group_mean = TRUE,
  reorder_legend = FALSE
)

Arguments

xf_rate	The 'rate_data' tibble as generated by 'revive_plate'
param	Either "OCR" or "ECAR"
normalize	Either TRUE or FALSE
normalize_unit	any string that will be pasted in the y-axis label when normalize = TRUE
take_group_mean	Either TRUE or FALSE
reorder_legend	Either TRUE or FALSE. When 'TRUE' the groups are ordered based on the number in the character string of the group. It also adds a "__00" after each character string to make the forcats::refactor(group, parse_number(group)) work.

Value

a ggplot object

Examples

system.file("extdata",
    "20191219_SciRep_PBMCs_donor_A.xlsx",
    package = "seahtrue"
) |>
    revive_xfplate() |>
    purrr::pluck("rate_data", 1) |>
    sketch_rate(
        param = "OCR",
        reorder_legend = TRUE
    )

system.file("extdata",
    "20191219_SciRep_PBMCs_donor_A.xlsx",
    package = "seahtrue"
) |>
    revive_xfplate() |>
    purrr::pluck("rate_data", 1) |>
    sketch_rate(
        param = "OCR",
        take_group_mean = FALSE,
        reorder_legend = TRUE
    )

system.file("extdata",
    "20191219_SciRep_PBMCs_donor_A.xlsx",
    package = "seahtrue"
) |>
    revive_xfplate() |>
    purrr::pluck("rate_data", 1) |>
    sketch_rate(
        param = "ECAR",
        normalize = TRUE,
        take_group_mean = TRUE,
        reorder_legend = TRUE
    )

system.file("extdata",
    "20191219_SciRep_PBMCs_donor_A.xlsx",
    package = "seahtrue"
) |>
    revive_xfplate() |>
    purrr::pluck("rate_data", 1) |>
    sketch_rate(
        param = "ECAR",
        normalize = TRUE,
        take_group_mean = FALSE,
        reorder_legend = TRUE
    )

---