Plate: Plate Object
In SerolyzeR: Reading, Quality Control and Preprocessing of MBA (Multiplex Bead Assay) Data
Plate R Documentation
Plate Object
Description
The Plate object represents a Luminex assay plate and stores data related to
its samples, analytes, metadata, and batch information. This object is typically
created by functions such as read_luminex_data(), process_file(), or process_dir().
It provides methods for accessing and manipulating data, including retrieving
specific analyte measurements, filtering by sample type, and performing
blank adjustments.
Public fields
plate_name(character(1))
Name of the plate. Set to the name of the file from which the plate was read.
analyte_names(character())
Names of the analytes that were examined on the plate.
sample_names(character())
Names of the samples that were examined on the plate. The order of the
samples in this vector is identical with order in the CSV source file.
batch_name(character(1))
Name of the batch to which the plate belongs.
plate_datetime(POSIXct())
A date and time when the plate was created by the machine
sample_locations(character())
Locations of the samples on the plate. This vector is in the same order
as the sample_names vector.
sample_types(character())
Types of the samples that were examined on the plate.
The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL).
This vector is in the same order as the sample_names vector.
If the Plate object is read using read_luminex_data, then the sample types
are usually detected based on the sample names according to the rules
described in translate_sample_names_to_sample_types.
dilutions(character())
A list containing names of the samples as keys and string representing dilutions as values.
The dilutions are represented as strings. This vector is in the same order as the sample_names vector.
dilution_values(numeric())
A list containing names of the samples as keys and numeric values representing dilutions as values.
It is in the same order as the sample_names vector.
default_data_type(character(1))
The default data type that will be returned by the get_data method.
By default is set to Median.
data(list())
A list containing dataframes with the data for each sample and analyte.
The possible data types - the keys of the list are:
c(Median, Net MFI, Count, Avg Net MFI, Mean, Peak).
In each dataframe, the rows represent samples and the columns represent analytes.
batch_info(list())
A list containing additional, technical information about the batch.
layout(character())
A list containing information about the layout of the plate.
The layout is read from the separate file and usually provides additional
information about the dilutions, sample names, and the sample layout
on the actual plate.
blank_adjusted(logical)
A flag indicating whether the blank values have been adjusted.
Methods
Public methods
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Method new()
Method to initialize the Plate object
Usage
Plate$new(
plate_name,
sample_names,
analyte_names,
batch_name = "",
plate_datetime = NULL,
sample_locations = NULL,
sample_types = NULL,
dilutions = NULL,
dilution_values = NULL,
default_data_type = NULL,
data = NULL,
batch_info = NULL,
layout = NULL
)
Arguments
plate_name(character(1))
Name of the plate.
By default is set to an empty string,
during the reading process it is set to the name
of the file from which the plate was read.
sample_names(character())
Names of the samples that were examined on the plate. Sample names are by default ordered by location in the plate, using the row-major order.
The first sample is the one in upper-left corner, then follows the ones in the first row, then the second row, and so on.
analyte_names(character())
Names of the analytes that were examined on the plate.
batch_name(character(1))
Name of the batch to which the plate belongs.
By default is set to an empty string, during the reading process it is set to
the batch field of the plate
plate_datetime(POSIXct())
Datetime object representing the date and time when the plate was created by the machine.
sample_locations(character())
Locations of the samples on the plate.
Sample locations are ordered in the same way as samples in the input CSV file.
sample_types(character())
Types of the samples that were examined on the plate.
The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL).
Sample types are ordered in the same way as the sample_names vector.
If the Plate object is initialised using the default methods ( read_luminex_data
or any of the processing methods: process_dir, process_file and process_plate)
the sample types are detected based on the sample names according to the rules described in translate_sample_names_to_sample_types.
dilutions(character())
A list containing names of the samples as keys and string representing dilutions as values.
The dilutions are represented as strings. The dilutions are ordered in the same way as the sample_names vector
dilution_values(numeric())
A list containing names of the samples as keys and numeric values representing dilutions as values.
The dilution values are ordered in the same way as the sample_names vector
default_data_type(character(1))
The default data type that will be returned by the get_data method.
By default is set to Median.
data(list())
A list containing dataframes with the data for each sample and analyte.
The possible data types - the keys of the list are
c(Median, Net MFI, Count, Avg Net MFI, Mean, Peak).
In each dataframe, the rows represent samples and the columns represent analytes.
Rows of each dataframe are ordered in the same way as the sample_names vector.
batch_info(list())
A list containing additional, technical information about the batch.
layout(character())
A list containing information about the layout of the plate.
The layout is read from the separate file and usually provides additional
information about the dilutions, sample names, and the sample layout
on the actual plate.
Method print()
Function prints the basic information about the plate
such as the number of samples and analytes
Usage
Plate$print(...)
Arguments
...Additional parameters to be passed to the print function
Print the summary of the plate
Method summary()
Function outputs basic information about the plate, such as
examination date, batch name, and sample types.
Usage
Plate$summary(..., include_names = FALSE)
Arguments
...Additional parameters to be passed to the print function
Get data for a specific analyte and sample type
include_namesIf include_names parameter is TRUE, a
part from count of control samples, provides also their names.
By default FALSE
Method get_data()
Function returns data for a specific analyte and sample.
Usage
Plate$get_data(
analyte,
sample_type = "ALL",
data_type = self$default_data_type
)
Arguments
analyteAn analyte name or its id of which data we want to extract.
If set to 'ALL' returns data for all analytes.
sample_typeis a type of the sample we want to extract data from.
The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL). Default value is ALL.
data_typeThe parameter specifying which data type should be returned.
This parameter has to take one of values:
c(Median, Net MFI, Count, Avg Net MFI, Mean, Peak).
What's more, the data_type has to be present in the plate's data
Default value is plate's default_data_type, which is usually Median.
Returns
Dataframe containing information about a given sample type and analyte
Get the string representation of dilutions
Method get_dilution()
Function returns the dilution represented as strings for a specific sample type.
Usage
Plate$get_dilution(sample_type)
Arguments
sample_typetype of the samples that we want to obtain the dilution for.
The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL) Default value is ALL.
Returns
A list containing names of the samples as keys and string representing dilutions as values.
Get the numeric representation of dilutions
Method get_dilution_values()
Function returns the dilution values for a specific sample type.
Usage
Plate$get_dilution_values(sample_type)
Arguments
sample_typetype of the samples that we want to obtain the dilution values for.
The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL) Default value is ALL.
Returns
A list containing names of the samples as keys and numeric values representing dilutions as values.
Adjust the MFI values by subtracting the background
Method blank_adjustment()
Function adjusts the values of samples (all samples excluding the blanks) by clamping the
values to the aggregated value of the BLANK samples for each analyte separately.
The purpose of this operation is to unify the data by clamping values below the background noise.
how this method works was inspired by the paper https://doi.org/10.1038/s41598-020-57876-0 which covers the quality control in the MBA.
In short, this operation firstly calculates the aggregate of MFI in the BLANK samples
(available methods are: min, max, mean, median)
and then replaces all values below this threshold with the threshold value.
Method does not modifies the data of type Count.
This operation is recommended to be performed before any further analysis, but is optional.
Skipping it before further analysis is allowed, but will result in a warning.
Usage
Plate$blank_adjustment(threshold = "max", in_place = TRUE)
Arguments
thresholdThe method used to calculate the background value for each analyte.
Every value below this threshold will be clamped to the threshold value.
By default max. Available methods are: min, max, mean, median.
in_placeWhether the method should produce new plate with adjusted
values or not, By default TRUE - operates on the current plate.
Method clone()
The objects of this class are cloneable with this method.
Usage
Plate$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
SerolyzeR documentation built on April 12, 2025, 2:11 a.m.
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| Plate | R Documentation |
Plate Object
Description
The Plate object represents a Luminex assay plate and stores data related to
its samples, analytes, metadata, and batch information. This object is typically
created by functions such as read_luminex_data(), process_file(), or process_dir().
It provides methods for accessing and manipulating data, including retrieving specific analyte measurements, filtering by sample type, and performing blank adjustments.
Public fields
plate_name(
character(1))
Name of the plate. Set to the name of the file from which the plate was read.analyte_names(
character())
Names of the analytes that were examined on the plate.sample_names(
character())
Names of the samples that were examined on the plate. The order of the samples in this vector is identical with order in the CSV source file.batch_name(
character(1))
Name of the batch to which the plate belongs.plate_datetime(
POSIXct())
A date and time when the plate was created by the machinesample_locations(
character())
Locations of the samples on the plate. This vector is in the same order as thesample_namesvector.sample_types(
character())
Types of the samples that were examined on the plate. The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL). This vector is in the same order as thesample_namesvector. If thePlateobject is read usingread_luminex_data, then the sample types are usually detected based on the sample names according to the rules described intranslate_sample_names_to_sample_types.dilutions(
character())
A list containing names of the samples as keys and string representing dilutions as values. The dilutions are represented as strings. This vector is in the same order as thesample_namesvector.dilution_values(
numeric())
A list containing names of the samples as keys and numeric values representing dilutions as values. It is in the same order as thesample_namesvector.default_data_type(
character(1))
The default data type that will be returned by theget_datamethod. By default is set toMedian.data(
list())
A list containing dataframes with the data for each sample and analyte. The possible data types - the keys of the list are:
c(Median, Net MFI, Count, Avg Net MFI, Mean, Peak).In each dataframe, the rows represent samples and the columns represent analytes.
batch_info(
list())
A list containing additional, technical information about the batch.layout(
character())
A list containing information about the layout of the plate. The layout is read from the separate file and usually provides additional information about the dilutions, sample names, and the sample layout on the actual plate.blank_adjusted(
logical)
A flag indicating whether the blank values have been adjusted.
Methods
Public methods
Method new()
Method to initialize the Plate object
Usage
Plate$new( plate_name, sample_names, analyte_names, batch_name = "", plate_datetime = NULL, sample_locations = NULL, sample_types = NULL, dilutions = NULL, dilution_values = NULL, default_data_type = NULL, data = NULL, batch_info = NULL, layout = NULL )
Arguments
plate_name(
character(1))
Name of the plate. By default is set to an empty string, during the reading process it is set to the name of the file from which the plate was read.sample_names(
character())
Names of the samples that were examined on the plate. Sample names are by default ordered by location in the plate, using the row-major order. The first sample is the one in upper-left corner, then follows the ones in the first row, then the second row, and so on.analyte_names(
character())
Names of the analytes that were examined on the plate.batch_name(
character(1))
Name of the batch to which the plate belongs. By default is set to an empty string, during the reading process it is set to thebatchfield of the plateplate_datetime(
POSIXct())
Datetime object representing the date and time when the plate was created by the machine.sample_locations(
character())
Locations of the samples on the plate. Sample locations are ordered in the same way as samples in the input CSV file.sample_types(
character())
Types of the samples that were examined on the plate. The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL). Sample types are ordered in the same way as thesample_namesvector.If the Plate object is initialised using the default methods (
read_luminex_dataor any of the processing methods:process_dir,process_fileandprocess_plate) the sample types are detected based on the sample names according to the rules described intranslate_sample_names_to_sample_types.dilutions(
character())
A list containing names of the samples as keys and string representing dilutions as values. The dilutions are represented as strings. The dilutions are ordered in the same way as thesample_namesvectordilution_values(
numeric())
A list containing names of the samples as keys and numeric values representing dilutions as values. The dilution values are ordered in the same way as thesample_namesvectordefault_data_type(
character(1))
The default data type that will be returned by theget_datamethod. By default is set toMedian.data(
list())
A list containing dataframes with the data for each sample and analyte. The possible data types - the keys of the list are
c(Median, Net MFI, Count, Avg Net MFI, Mean, Peak). In each dataframe, the rows represent samples and the columns represent analytes. Rows of each dataframe are ordered in the same way as thesample_namesvector.batch_info(
list())
A list containing additional, technical information about the batch.layout(
character())
A list containing information about the layout of the plate. The layout is read from the separate file and usually provides additional information about the dilutions, sample names, and the sample layout on the actual plate.
Method print()
Function prints the basic information about the plate such as the number of samples and analytes
Usage
Plate$print(...)
Arguments
...Additional parameters to be passed to the print function Print the summary of the plate
Method summary()
Function outputs basic information about the plate, such as examination date, batch name, and sample types.
Usage
Plate$summary(..., include_names = FALSE)
Arguments
...Additional parameters to be passed to the print function Get data for a specific analyte and sample type
include_namesIf
include_namesparameter isTRUE, a part from count of control samples, provides also their names. By defaultFALSE
Method get_data()
Function returns data for a specific analyte and sample.
Usage
Plate$get_data( analyte, sample_type = "ALL", data_type = self$default_data_type )
Arguments
analyteAn analyte name or its id of which data we want to extract. If set to 'ALL' returns data for all analytes.
sample_typeis a type of the sample we want to extract data from. The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL). Default value isALL.data_typeThe parameter specifying which data type should be returned. This parameter has to take one of values:
c(Median, Net MFI, Count, Avg Net MFI, Mean, Peak). What's more, thedata_typehas to be present in the plate's data Default value is plate'sdefault_data_type, which is usuallyMedian.
Returns
Dataframe containing information about a given sample type and analyte Get the string representation of dilutions
Method get_dilution()
Function returns the dilution represented as strings for a specific sample type.
Usage
Plate$get_dilution(sample_type)
Arguments
sample_typetype of the samples that we want to obtain the dilution for. The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL)Default value isALL.
Returns
A list containing names of the samples as keys and string representing dilutions as values. Get the numeric representation of dilutions
Method get_dilution_values()
Function returns the dilution values for a specific sample type.
Usage
Plate$get_dilution_values(sample_type)
Arguments
sample_typetype of the samples that we want to obtain the dilution values for. The possible values are
c(ALL, BLANK, TEST, NEGATIVE CONTROL, STANDARD CURVE, POSITIVE CONTROL)Default value isALL.
Returns
A list containing names of the samples as keys and numeric values representing dilutions as values.
Adjust the MFI values by subtracting the background
Method blank_adjustment()
Function adjusts the values of samples (all samples excluding the blanks) by clamping the
values to the aggregated value of the BLANK samples for each analyte separately.
The purpose of this operation is to unify the data by clamping values below the background noise. how this method works was inspired by the paper https://doi.org/10.1038/s41598-020-57876-0 which covers the quality control in the MBA.
In short, this operation firstly calculates the aggregate of MFI in the BLANK samples
(available methods are: min, max, mean, median)
and then replaces all values below this threshold with the threshold value.
Method does not modifies the data of type Count.
This operation is recommended to be performed before any further analysis, but is optional. Skipping it before further analysis is allowed, but will result in a warning.
Usage
Plate$blank_adjustment(threshold = "max", in_place = TRUE)
Arguments
thresholdThe method used to calculate the background value for each analyte. Every value below this threshold will be clamped to the threshold value. By default
max. Available methods are:min,max,mean,median.in_placeWhether the method should produce new plate with adjusted values or not, By default
TRUE- operates on the current plate.
Method clone()
The objects of this class are cloneable with this method.
Usage
Plate$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
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