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Title: RT-QuIC Data Formatting and Analysis
Version: 2.1.0
Description: Designed for the curation and analysis of data generated from real-time quaking-induced conversion (RT-QuIC) assays first described by Atarashi et al. (2011) <doi:10.1038/nm.2294>. 'quicR' calculates useful metrics such as maxpoint ratio: Rowden et al. (2023) <doi:10.1099/vir.0.069906-0>; time-to-threshold: Shi et al. (2013) <doi:10.1186/2051-5960-1-44>; and maximum slope. Integration with the output from plate readers allows for seamless input of raw data into the R environment.
Imports: dplyr, ggplot2, janitor, openxlsx, purrr, readxl, reshape2, slider, stats, stringr, tidyr
Depends: R (≥ 4.1.0)
License: GPL-3
Encoding: UTF-8
RoxygenNote: 7.3.2
Suggests: testthat (≥ 3.1.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2025-02-26 19:16:47 UTC; rowde002
Author: Gage Rowden ORCID iD [aut, cre]
Maintainer: Gage Rowden <gage.rowden1145@gmail.com>
Repository: CRAN
Date/Publication: 2025-02-26 19:30:02 UTC

@description Data handling for real-time quaking induced conversion assays

Description

See the README on Github

Details

@keywords internal

Author(s)

Maintainer: Gage Rowden gage.rowden1145@gmail.com (ORCID)

Format Table for BMG Sample ID Import

Description

BMG_format accepts a plate layout .CSV file and formats the Sample IDs into a format which can be easily imported into the BMG control software.

Usage

BMG_format(
  file,
  save_path = "",
  save_name = "formatted.txt",
  write_file = FALSE
)

Arguments

file

A .CSV file containing the plate layout of Sample IDs.

save_path

The path to the directory that you want the file saved.

save_name

The name of the output file. Should have the ".txt" extension.

write_file

Logical. If true, function will write a .txt file; otherwise it will return a character vector.

Value

A text file containing information for import into the BMG control software.

Examples

layout_file <- system.file(
  "extdata/BMG_formatting",
  file = "plate_layout.csv",
  package = "quicR"
)
BMG_format(layout_file)

Add replicates

Description

Adds replicate information to the sample IDs. Well IDs should be formatted like so: A4, B9, H11, J24

Usage

add_reps(df, sep = "_")

Arguments

df

A dataframe containing two columns for well IDs and Sample IDs

sep

a character string to separate the terms.

Value

A dataframe with replicate numbers pasted to the Sample IDs

Calculate the Maxpoint Ratio

Description

Maxpoint ratio is defined as the maximum relative fluorescence divided by the background fluorescence.

Usage

calculate_MPR(data, start_col = 3, data_is_norm = TRUE)

Arguments

data

A dataframe containing the real-time fluorescence data.

start_col

Integer, the column at which the background fluorescence should be read.

data_is_norm

Logical, if the data has not been normalized, will make a call to normalize_RFU.

Value

A vector containing MPR values.

Examples

# This test takes >5 sec

file <- system.file(
  "extdata/input_files",
  file = "test.xlsx",
  package = "quicR"
)
df_ <- quicR::get_real(file)[[1]]
print(calculate_MPR(df_))

Calculate Maximum Slope

Description

Uses a sliding window to calculate the slope of real-time reads.

Usage

calculate_MS(data, window = 3, data_is_norm = TRUE)

Arguments

data

A dataframe containing real-time reads. It is recommended to use a dataframe made from normalize_RFU.

window

Integer designating how wide you want the sliding window to be for calculating the moving average slope.

data_is_norm

Logical; if FALSE, will make a call to normalize_RFU.

Value

A dataframe containing the real-time slope values as change in RFU/sec.

Examples

# This test takes >5 sec

file <- system.file(
  "extdata/input_files",
  file = "rt_data.csv",
  package = "quicR"
)
df_ <- read.csv(file, check.names = FALSE)
calculate_MS(df_)

Calculate Time to Threshold

Description

Calculates the time required to reach a defined threshold.

Usage

calculate_TtT(data, threshold, start_col = 3)

Arguments

data

A dataframe containing real-time RT-QuIC data.

threshold

A numeric value defining the threshold.

start_col

The column containing the starting position of the real-time data.

Value

A vector containing the times to threshold

Examples

# This test takes >5 sec

file <- system.file(
  "extdata/input_files",
  file = "test2.xlsx",
  package = "quicR"
)
df_ <- get_real(file)[[1]] |>
  quicR::transpose_real() |>
  quicR::normalize_RFU(transposed = TRUE)
calculate_TtT(df_, threshold = 2)

Generate a dataframe with calculated metrics.

Description

Uses functions from the "calculate" family of quicR functions to generate an analyzed dataframe.

Usage

calculate_metrics(
  data,
  meta,
  metrics = c("MPR", "MS", "TtT", "RAF"),
  transpose = FALSE,
  normalize = FALSE,
  start_col = 3L,
  MS_window = 3L,
  threshold = 2
)

Arguments

data

A dataframe containing the raw RT-QuIC data.

meta

A dataframe containing sample metadata. Should include at least the "Sample IDs" column.

metrics

An array containing the metrics which should be calculated.

transpose

Logical; should the raw data be transposed before performing the calculations?

normalize

Logical; should the raw data be normalized before performing the calculations?

start_col

Integer; column number denoting where the numeric data begins.

MS_window

Integer; width of the window applied in the calculation of max slope.

threshold

Float; the threshold applied to the calculation of time-to-threshold.

Value

A dataframe of calculated metrics.

Examples

file <- system.file(
  "extdata/input_files",
  file = "test4.xlsx",
  package = "quicR"
)

data <- quicR::get_real(file)[[1]] |>
  quicR::normalize_RFU()

meta <- quicR::organize_tables(file) |>
  quicR::convert_tables()

calculate_metrics(data, meta)

Calculate a Threshold for Rate Determination

Description

Calculates a threshold for determining time-to-threshold and rate of amyloid formation.

Usage

calculate_threshold(
  data,
  background_cycle = 2,
  method = list("stdev", "none"),
  multiplier = 1
)

Arguments

data

A dataframe output from get_real.

background_cycle

Integer; the cycle used for background fluorescence.

method

Method for determining threshold; default is "stdev".

multiplier

For some methods, will add a multiplier for more conservative thresholds.

Value

A float value.

Examples

file <- system.file(
  "extdata/input_files",
  file = "test2.xlsx",
  package = "quicR"
)
threshold <- get_real(file)[[1]] |>
  calculate_threshold(multiplier = 10)

Convert tables into a single column in a dataframe.

Description

Accepts a table or matrix or a list of tables and matrices and converts them into dataframe columns.

Usage

convert_tables(tab, na_omit = TRUE)

Arguments

tab

A table/matrix or a list of tables/matrices.

na_omit

Logical; if true, will remove rows with NA.

Value

A dataframe column.

Examples

file <- system.file(
  "extdata/input_files",
  file = "test.xlsx",
  package = "quicR"
)
tabs <- organize_tables(file)
convert_tables(tabs)

Retrieve the BMG metadata

Description

Takes the Excel file exported from MARS and compiles the metadata in the header.

Usage

get_meta(file)

Arguments

file

The Excel file exported from MARS.

Value

A dataframe containing the Meta_ID and Meta_info

Examples

file <- system.file(
  "extdata/input_files",
  file = "test.xlsx",
  package = "quicR"
)
get_meta(file)

Get Real-Time RT-QuIC Fluorescence Data

Description

Accepts an Excel file or a dataframe of real-time RT-QuIC data.

Usage

get_real(data, ordered = FALSE)

Arguments

data

Either an Excel file or a dataframe.

ordered

Logical, if true, will organize the columns by sample ID rather than by well.

Value

A list of dataframes containing the formatted real-time data.

Examples

file <- system.file(
  "extdata/input_files",
  file = "test.xlsx",
  package = "quicR"
)
get_real(file)

Get the well locations of the samples used in the RT-QuIC run.

Description

Returns a dataframe with the sample IDs and well IDs used in the plate.

Usage

get_sample_locations(
  file,
  tab_name = "Sample IDs",
  dilution_bool = FALSE,
  dilution_fun = function(x) 1 * x,
  sep = "\n",
  plate = 96
)

Arguments

file

Excel file exported from MARS

tab_name

Table name containing the sample IDs.

dilution_bool

Logical; is there a table containing dilution factors? If so, will add a newline and the log of the dilution factor to the ID column.

dilution_fun

A function for transforming the dilution factor.

sep

A string used to separate the sample ID and dilution factor.

plate

Integer; either 96 or 384 to denote microplate type.

Value

A vector containing well IDs.

Examples

file <- system.file(
  "extdata/input_files",
  file = "test.xlsx",
  package = "quicR"
)
get_sample_locations(file)

Get the Wells Used in the RT-QuIC Run.

Description

Returns the well IDs used in the plate.

Usage

get_wells(file)

Arguments

file

Excel file exported from MARS

Value

A vector containing well IDs.

Examples

file <- system.file(
  "extdata/input_files",
  file = "test.xlsx",
  package = "quicR"
)
get_wells(file)

Normalize Fluorescence

Description

Normalizes the real-time RT-QuIC data against the background fluorescence of a defined cycle. All cycles are divided by the fluorescent value of the defined cycle.

Usage

normalize_RFU(data, bg_cycle = 4, transposed = FALSE)

Arguments

data

A dataframe generated from get_real.

bg_cycle

The cycle used for background fluorescence

transposed

Logical, TRUE if cycle values are shown as column names.

Value

A dataframe containing real-time normalized fluorescence values.

Examples

# This test takes >5 sec

file <- system.file(
  "extdata/input_files",
  file = "test2.xlsx",
  package = "quicR"
)
df_ <- get_real(file)[[1]]

# Export the tables in the first sheet of the file.
dic <- quicR::organize_tables(file)

# Normalize the raw data against the background reading.
normalize_RFU(df_)

Organize MARS Tables

Description

Extracts the tables from the microplate view sheet in the MARS Excel file and adds each table to a list.

Usage

organize_tables(file, plate = 96)

Arguments

file

An Excel file exported from MARS.

plate

Integer either 96 or 384 to denote microplate type.

Value

A list containing tibbles.

Examples

file <- system.file(
  "extdata/input_files",
  file = "test.xlsx",
  package = "quicR"
)
organize_tables(file)

Real-Time Plate View

Description

Converts the real-time data into a ggplot figure. The layout is either 8x12 or 16x24 for 96- and 384-well plates, respectively.

Usage

plate_view(df, meta, plate = 96)

Arguments

df

Real-time dataframe

meta

Dataframe containing well IDs and Sample IDs to title each facet.

plate

Integer either 96 or 384 to denote microplate type.

Value

A ggplot object

Examples

# This test takes >5 sec

file <- system.file(
  "extdata/input_files",
  file = "test2.xlsx",
  package = "quicR"
)

# Get the real-time data.
df_ <- get_real(file, ordered = FALSE)[[1]] |>
  as.data.frame()

sample_locations <- get_sample_locations(
  file,
  dilution_bool = TRUE,
  dilution_fun = function(x) -log10(x)
)

plate_view(df_, sample_locations)

Plot metrics generated from the "calculate" family of quicR functions.

Description

Generates a faceted figure of boxplots.

Usage

plot_metrics(
  data,
  sample_col = "Sample IDs",
  fill = "Dilutions",
  dilution_bool = TRUE,
  nrow = 2,
  ncol = 2
)

Arguments

data

A dataframe containing the calculated metrics from the "calculate" family of quicR functions.

sample_col

The name of the column containing the sample IDs.

fill

The column containing the fill aesthetic. Usually the dilutions column.

dilution_bool

Logical; should dilution factors be included in the plot?

nrow

Integer; number of rows to output in the plot.

ncol

Integer; number of columns to output in the plot.

Value

A ggplot object

Examples

# This test takes >5 sec

file <- system.file(
  "extdata/input_files",
  file = "test4.xlsx",
  package = "quicR"
)

data <- quicR::get_real(file)[[1]] |>
  quicR::normalize_RFU()

meta <- quicR::organize_tables(file) |>
  quicR::convert_tables()

calculate_metrics(data, meta) |>
  plot_metrics()

Separate Real-Time Data into separate dataframes.

Description

If multiple real-time reads were exported from MARS, separate_raw will parse them out and separate them. It will also export to an Excel file with each real-time data having its own sheet.

Usage

separate_raw(file, num_rows, export_name)

Arguments

file

An Excel file exported from MARS.

num_rows

Number of rows in the header to ignore.

export_name

The name of the original file or an orignal name.

Value

An Excel file with separated raw real-time data.

Transpose Real-Time Data

Description

Transposes the real-time data table exported by the BMG software. Accepts output from the function, "get_real".

Usage

transpose_real(data)

Arguments

data

A dataframe generated from get_real.

Value

A transposed dataframe containing real-time normalized fluorescence values.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.