Help for package dPCP

Title:

Automated Analysis of Multiplex Digital PCR Data

Version:

2.0.1

Description:

The automated clustering and quantification of the digital PCR data is based on the combination of 'DBSCAN' (Hahsler et al. (2019) <doi:10.18637/jss.v091.i01>) and 'c-means' (Bezdek et al. (1981) <doi:10.1007/978-1-4757-0450-1>) algorithms. The analysis is independent of multiplexing geometry, dPCR system, and input amount. The details about input data and parameters are available in the vignette.

License:

MIT + file LICENSE

Encoding:

UTF-8

Depends:

R (≥ 4.0.0)

Imports:

cluster, dbscan, e1071, exactci, ggplot2, ggpubr, graphics, raster, rlist, scales, shiny, shinyjs, stats, stringr, utils

RoxygenNote:

7.2.1

Suggests:

knitr, rmarkdown, testthat

VignetteBuilder:

knitr

URL:

https://github.com/alfodefalco/dPCP

BugReports:

https://github.com/alfodefalco/dPCP/issues

NeedsCompilation:

Packaged:

2023-08-12 17:53:04 UTC; alfonsodefalco

Author:

Alfonso De Falco

[aut, cre], Michel Mittelbronn [ctb], Christophe Olinger [ctb], Daniel Stieber [ctb], Laboratoire national de santé [cph]

Maintainer:

Alfonso De Falco <alfonsodefalco90@gmail.com>

Repository:

CRAN

Date/Publication:

2023-08-12 18:20:02 UTC

Prediction of clusters centroid position

Description

This function calculates the coodintaes of all clusters centroid.

Usage

centers_data(sample.subquality, sample.table, referenceDB)

## S3 method for class 'centers_data'
plot(x, ..., sample = "all")

Arguments

sample.subquality

an object of class read_sample, inherited from read_sample.

sample.table

object of class sample_table, inherited from read_sampleTable.

referenceDB

an object of class reference_dbscan, inherited from reference_dbscan

x

an object of class centers_data

...

Arguments to be passed to methods

sample

'all' to show all samples, or a numeric vector indicating the row number of samples in the sample table.

Value

An object of class centers_data containing a sublist for each sample. Each sublist has the following components:

quality

quality threshold used in read_sample.

reference

reference ID.

centers

a data frame with the centroids coordinates.

data

a data frame with the fluorescence intensities.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata",package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

#Read reference files
ref <- read_reference(sample.table, system = "bio-rad",
                      file.location = fileLoc)

#Read samples files
samp <- read_sample(sample.table, system = "bio-rad",
                    file.location = fileLoc)

#Reference DBSCAN clustering
dbref <- reference_dbscan(ref, sample.table, save.template = FALSE)

#Predict position of clusters centroid from reference DBSCAN results
cent <- centers_data(samp, sample.table,dbref)

plot(cent, sample = "all")

Cluster analysis with fuzzy c-means algorithm

Description

This function carries out the c-means cluster analysis, using the centroids position as initial values for cluster centers.

Usage

cmeans_clus(centers.data)

## S3 method for class 'cmeans_clus'
plot(x, ..., sample = "all", color.blind = FALSE)

Arguments

centers.data

an object of class centers_data, inherited from centers_data.

x

an object of class cmeans_clus

...

Arguments to be passed to methods

sample

'all' to show all samples, or a numeric vector indicating the row number of samples in the sample table.

logical. If TRUE colors optimized for colorblind readers are used.

Value

An object of class cmeans_clus containing a sublist for each sample. Each sublist has the following components:

quality

quality threshold used in read_sample.

reference

reference ID.

centers

a data frame with the centroids coordinates.

data

a data frame with the fluorescence intensities and clusters name.

membership

a matrix with the membership values of the data elements to the clusters. See also cmeans

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata",package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

#Read reference files
ref <- read_reference(sample.table, system = "bio-rad",
                      file.location = fileLoc)

#Read samples files
samp <- read_sample(sample.table, system = "bio-rad",
                    file.location = fileLoc)

#Reference DBSCAN clustering
dbref <- reference_dbscan(ref, sample.table, save.template = FALSE)

#Predict position of clusters centroid from reference DBSCAN results
cent <- centers_data(samp, sample.table,dbref)

#Fuzzy c-means clustering
cmclus <- cmeans_clus(cent)

plot(cmclus, sample = "all")

Automated analysis of digital PCR data

Description

This function carries out the autometed clustering of digital PCR data.

Usage

dPCP(
  file,
  system = NULL,
  file.location = ".",
  reference.quality = 0.5,
  sample.quality = 0.5,
  eps = 200,
  minPts = 50,
  save.template = FALSE,
  rain = TRUE,
  QC.reference = FALSE,
  partition.volume = NULL
)

## S3 method for class 'dPCP'
plot(
  x,
  ...,
  sample = "all",
  reference = "all",
  type = "dPCP",
  color.blind = FALSE
)

Arguments

file

character. The name or the path of csv file to be read. If it does not contain an absolute path, the file name is relative to the current working directory, (getwd).

system

character. The name of digital PCR system used to generate the data. It must be either Thermo Fisher or Bio-Rad. Abbreviations are also accepted.

file.location

character. Full path name to reference and sample files location. The default corresponds to the working directory, (getwd). Tilde expansion (see (path.expand)) is performed.

reference.quality

numeric. Between 0 and 1. Quality threshold to subset the data. If different thresholds have to be applied to various reference samples, a vectror of the same length of number of reference samples has to be provided. Used only when the system is Thermo Fisher.

sample.quality

numeric. Between 0 and 1. Quality threshold to subset data. If different thresholds have to be applied to various samples, a vectror of the same length of number of samples has to be provided. Used only when the system is Thermo Fisher.

eps

numeric. Input parameter for the DBSCAN algorithm. It represents the maximum distance between the elements within a cluster. See also dbscan. If different values have to be applied to various reference samples, a vectror of the same length of number of reference samples has to be provided.

minPts

numeric. Input parameter for the DBSCAN algorithm. It represents the number of minimum elements to assemble a cluster. See also dbscan. If different values have to be applied to various reference samples, a vectror of the same length of number of reference samples has to be provided.

save.template

logical. If TRUE a template of DBSCAN analysis of reference samples is saved. When system is Thermo Fisher, save.template can be also a character vector indicating the chipID.

rain

logical. If TRUE the rain analysis is carried out.

QC.reference

logical. If TRUE the fraction of rain elements in the reference samples is carried out. Warning messages are displayed when the percentage of rain is high.

partition.volume

numeric. This parameters is taken into account when the parameter 'system' is set on Other. Indicate the partion volume in microliters spcific to the digital PCR system.

x

an object of class dPCP

...

Arguments to be passed to methods

sample

'all' to show all samples, or a numeric vector indicating the row number of samples in the sample table.

reference

'all' to show all reference samples, or a character vector with chip ID (Thermo Fisher) or the file name (Bio-rad) of reference samples to be showed.

type

string. Type of plot to be showed. Available plots: 'reference dbscan', 'centers', 'cmeans', 'rain', 'dPCP'. @param color.blind logical. If TRUE colors optimized for colorblind readers are used.

logical. If TRUE colors optimized for colorblind readers are used.

Value

An object of class dPCP containing the following components:

referenceDB

an object of class reference_dbscan.

samples

a list of samples. Each sample sublist contains the information about the cluster analysis.

results

an object of class replicates_quant.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata", package = "dPCP")

#dPCP analysis
results <- dPCP(sampleTable, system = "bio-rad", file.location = fileLoc,
                eps = 200, minPts = 50, save.template = FALSE, rain = TRUE,
                QC.reference = FALSE)

plot(results, sample = 1, type = "dPCP")

Test eps and minPts combinations for DBSCAN analysis

Description

This function tests all combinations of eps and minPts for DBSCAN analysis of reference samples indicated in refID. The results are represented in scatterplots exported to a pdf file.

Usage

dbscan_combination(
  refID,
  system = NULL,
  file.location = ".",
  reference.quality = 0.5,
  eps = c(120, 150, 180, 200),
  minPts = c(20, 50, 80, 100)
)

Arguments

refID

a string or a character vector of chipID (Thermo Fisher) or the complete file name with the extension (Bio-Rad) of reference sample(s) to be analysed.

system

character. The name of digital PCR system used to generate the data. It must be either Thermo Fisher or Bio-Rad. Abbreviations are also accepted.

file.location

character. Full path name to reference and sample files location. The default corresponds to the working directory, (getwd). Tilde expansion (see (path.expand)) is performed.

reference.quality

numeric. Between 0 and 1. Quality threshold to subset the data (just for Thermo Fisher). If different thresholds have to be applied to various reference samples, a vectror of the same length of refID has to be provided.

eps

a numeric vector of values to be tested. Maximum distance between elements within a cluster in a DBSCAN analysis. See also dbscan.

minPts

a numeric vector of values to be tested. Number of minimum elements to assemble a cluster in a DBSCAN analysis. See also dbscan.

Value

A pdf file containing the scatterplots of DBSCAN analysis performed with all combinations of eps and minPts. Each reference generates a different pdf file.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata", package = "dPCP")

dbscan_combination("dilution20200313_B01_Amplitude.csv",
                   file.location = fileLoc, system = "bio-rad",
                   eps = c(150, 160, 180, 190), minPts = c(80, 100, 120))

unlink("dilution20200313_B01_Amplitude.pdf")

Export dPCP analysis results to a csv file

Description

This function exports dPCP analysis results to a csv file.

Usage

export_csv(data, filename)

Arguments

data

an object of class dPCP, target_quant or replicates_quant.

filename

character. File name (no extension) for csv and pdf files to create on disk.

Value

A csv file with the information and results of dPCP analysis.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata",package = "dPCP")

#dPCP analysis
results <- dPCP(sampleTable, system = "bio-rad", file.location = fileLoc,
                eps = 200, minPts = 50, save.template = FALSE,
                rain = TRUE)

export_csv(results, filename = "dPCRproject_1")

Manual correction of dPCP cluster analysis

Description

This function builds an interactive app to manually correct the dPCP cluster analysis.

Usage

manual_correction(
  data,
  filename,
  save.plot = FALSE,
  format = "png",
  dpi = 300,
  color.blind = FALSE
)

Arguments

data

an object of class dPCP, inherited from dPCP.

filename

character. File name (no extension) for csv and pdf files to create on disk.

save.plot

logical. If TRUE the plots are exported to a file.

format

a string indicating the file format for the export. Available formats: 'eps', 'ps', 'tex', 'pdf', 'jpeg', 'tiff', 'png', 'bmp', 'svg', 'wmf'.

dpi

numeric. Image resolution.

logical. If TRUE colors optimized for colorblind readers are used.

Value

A Shiny session.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata",package = "dPCP")

#dPCP analysis
results <- dPCP(sampleTable, system = "bio-rad", file.location = fileLoc,
                eps = 200, minPts = 50, save.template = FALSE,
                rain = TRUE)

manual_correction(results, filename = "manual_dPCR", save.plot = FALSE)

Identification and clustering of "rain" data

Description

This function identifies the "rain" elements and re-clusters them using the Mahalanobis distance. Each "rain" element is assigned to the cluster whose Mahalanobis distance is the lowest.

Usage

rain_reclus(cmeans.cluster)

## S3 method for class 'rain_reclus'
plot(x, ..., sample = "all", color.blind = FALSE)

Arguments

cmeans.cluster

an object of class cmeans_clus, inherited from cmeans_clus.

x

an object of class rain_reclus

...

Arguments to be passed to methods

sample

'all' to show all samples, or a numeric vector indicating the row number of samples in the sample table.

logical. If TRUE colors optimized for colorblind readers are used.

Value

An object of class rain_reclus containing a sublist for each sample. Each sublist has the following components:

quality

quality threshold used in read_sample.

reference

reference ID.

centers

a data frame with the centroids coordinates.

data

a data frame with the fluorescence intensities and clusters name.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata",package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

#Read reference files
ref <- read_reference(sample.table, system = "bio-rad",
                      file.location = fileLoc)

#Read samples files
samp <- read_sample(sample.table, system = "bio-rad",
                   file.location = fileLoc)

#Reference DBSCAN clustering
dbref <- reference_dbscan(ref, sample.table, save.template = FALSE)

#Predict position of clusters centroid from reference DBSCAN results
cent <- centers_data(samp, sample.table,dbref)

#Fuzzy c-means clustering
cmclus <- cmeans_clus(cent)

#Rain classification.
rainclus <- rain_reclus(cmclus)

plot(rainclus, sample = "all")

Read reference files

Description

This function reads the results files of reference samples listed in the sample table. Fluoresce intensity and quality value (just for Thermo Fisher) are collected. If a reference_dbscan template file with the same input paramters (reference ID, eps, minPts) is available, fluorescence data, quality value and dbscan analysis results are retrived from the template file.

Usage

read_reference(
  sample.table,
  system = NULL,
  file.location = ".",
  reference.quality = 0.5,
  eps = NULL,
  minPts = NULL
)

Arguments

sample.table

object of class sample_table, inherited from read_sampleTable.

system

character. The name of digital PCR system used to generate the data. It must be either Thermo Fisher or Bio-Rad. Abbreviations are also accepted.

file.location

character. Full path name to reference and sample files location. The default corresponds to the working directory, (getwd). Tilde expansion (see (path.expand)) is performed.

reference.quality

eps, minPts

numeric. Input parameters for the DBSCAN algorithm. If they match the paramters of reference_dbscan template file, the data are retrived from the template.

Value

An object of class read_reference containing a sublist for each reference. Each sublist has the following components:

quality

value of the reference.quality parameter.

data

a matrix with the fluorescence intensities and quality values.

dbscan

an object of class dbscan_fast, inherited from dbscan. This component is available only if a reference_dbscan template file is used to retrive the data.

Examples

library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata", package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

#Read reference files
ref <- read_reference(sample.table, system = "bio-rad",
                      file.location = fileLoc)

Read sample files

Description

This function reads the results files of samples listed in the sample table. Fluoresce intensity and quality value (just for Thermo Fisher) are collected.

Usage

read_sample(
  sample.table,
  system = NULL,
  file.location = ".",
  sample.quality = 0.5,
  partition.volume = NULL
)

Arguments

sample.table

object of class sample_table, inherited from read_sampleTable.

system

character. The name of digital PCR system used to generate the data. It must be either Thermo Fisher or Bio-Rad. Abbreviations are also accepted.

file.location

character. Full path name to reference and sample files location. The default corresponds to the working directory, (getwd). Tilde expansion (see (path.expand)) is performed.

sample.quality

partition.volume

numeric. This parameters is taken into account when the parameter 'system' is set on Other. Indicate the partion volume in microliters spcific to the digital PCR system.

Value

An object of class read_sample containing a sublist for each sample. Each sublist has the following components:

quality

value of the sample.quality parameter.

data

a matrix with the fluorescence intensities and quality values.

Examples

library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata", package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

#Read reference files
ref <- read_reference(sample.table, system = "bio-rad",
                      file.location = fileLoc)

#Read samples files
samp <- read_sample(sample.table, system = "bio-rad",
                    file.location = fileLoc)

Read sample table

Description

This function reads a file containing the essential information about the samples and experimental settings. The file has to be filled out by the user and formatted as described in the vignette.

Usage

read_sampleTable(file, system = NULL, file.location = ".")

Arguments

file

character. The name or the path of csv file to be read. If it does not contain an absolute path, the file name is relative to the current working directory, (getwd).

system

character. The name of digital PCR system used to generate the data. It must be either Thermo Fisher or Bio-Rad. Abbreviations are also accepted.

file.location

character. Full path name to reference and sample files location. The default corresponds to the working directory, (getwd). Tilde expansion (see (path.expand)) is performed.

Value

An object of class sample_table.

Examples

library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata", package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

Find the empty partitions and single target clusters in the reference sample

Description

This function computes a DBSCAN analysis to identify single target clusters in the reference samples listed in the sample table. If a reference_dbscan template file with the same input paramters (reference ID, eps, minPts) is available, data are retrived from the template file.

Usage

reference_dbscan(
  reference.subquality,
  sample.table,
  eps = 200,
  minPts = 50,
  save.template = FALSE
)

## S3 method for class 'reference_dbscan'
plot(x, ..., reference = "all")

Arguments

reference.subquality

an object of class read_reference, inherited from read_reference.

sample.table

object of class sample_table, inherited from read_sampleTable.

eps, minPts

numeric. Input parameters for the DBSCAN algorithm. If they match the paramters of reference_dbscan template file, the data are retrived from the template.

save.template

logical. If TRUE a template of DBSCAN analysis of reference samples is saved. When system is Thermo Fisher, save.template can be also a character vector indicating the chipID.

x

an object of class reference_dbscan

...

Arguments to be passed to methods

reference

'all' to show all reference samples, or a character vector with chip ID (Thermo Fisher) or the file name (Bio-rad) of reference samples to be showed.

Value

An object of class reference_dbscan containing a sublist for each reference. Each sublist has the following components:

quality

quality threshold used in read_reference.

data

a matrix with the fluorescence intensities and quality values.

dbscan

an object of class dbscan_fast, inherited from dbscan.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata",package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

#Read reference files
ref <- read_reference(sample.table, system = "bio-rad",
                      file.location = fileLoc)

#Read samples files
samp <- read_sample(sample.table, system = "bio-rad",
                    file.location = fileLoc)

#Reference DBSCAN clustering
dbref <- reference_dbscan(ref, sample.table, save.template = FALSE)

plot(dbref, reference = "all")

Calculation of targets concentration, pooling the sample replicates

Description

This function calculates the concentration of the targets, combining the results of the replicates of each sample.

Usage

replicates_quant(raw.results, sample.table)

Arguments

raw.results

an object of class target_quant, inherited from target_quant.

sample.table

object of class sample_table, inherited from read_sampleTable.

Value

An object of class replicates_quant containing a sublist for every sample. Each sublist has the following components:

quality

quality threshold used in read_sample.

reference

reference ID.

raw results

a data frame with the results of quantification.

replicates results

a data frame with the results of quantification of pooled replicates.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata", package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

#Read reference files
ref <- read_reference(sample.table, system = "bio-rad",
                      file.location = fileLoc)

#Read samples files
samp <- read_sample(sample.table, system = "bio-rad",
                   file.location = fileLoc)

#Reference DBSCAN clustering
dbref <- reference_dbscan(ref, sample.table, save.template = FALSE)

#Predict position of clusters centroid from reference DBSCAN results
cent <- centers_data(samp, sample.table,dbref)

#Fuzzy c-means clustering
cmclus <- cmeans_clus(cent)

#Rain classification.
rainclus <- rain_reclus(cmclus)

#Quantification
quantcm <- target_quant(cmclus, sample.table)
quant <- target_quant(rainclus, sample.table)

#Replicates pooling
rep.quant <- replicates_quant(quant, sample.table)

Export dPCP analysis results to a pdf report

Description

This function generates a pdf report of the dPCP analysis.

Usage

report_dPCP(data, filename, sample = "all", color.blind = FALSE)

Arguments

data

an object of class dPCP, inherited from dPCP.

filename

character. File name (no extension) for csv and pdf files to create on disk.

sample

'all' to show all samples, or a numeric vector indicating the row number of samples in the sample table.

logical. If TRUE colors optimized for colorblind readers are used.

Value

A pdf file with the information and results of the dPCP analysis.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata", package = "dPCP")

#dPCP analysis
results <- dPCP(sampleTable, system = "bio-rad", file.location = fileLoc,
                eps = 200, minPts = 50, save.template = FALSE,
                rain = TRUE)

report_dPCP(results, filename = "dPCRproject_1")

Calculation of targets concentration.

Description

This function calculates the concentration of the targets according to the Poisson distribution.

Usage

target_quant(data.cluster, sample.table)

Arguments

data.cluster

an object of class rain_reclus or cmeans_clus.

sample.table

object of class sample_table, inherited from read_sampleTable.

Value

An object of class target_quant containing a sublist for each sample. Each sublist has the following components:

quality

quality threshold used in read_sample.

reference

reference ID.

raw results

a data frame with the results of the quantification.

Examples


library(dPCP)

#Find path of sample table and location of reference and input files
sampleTable <- system.file("extdata", "Template_sampleTable.csv",
                     package = "dPCP")

fileLoc <- system.file("extdata", package = "dPCP")

#Read sample table file
sample.table <- read_sampleTable(sampleTable, system = "bio-rad",
                                 file.location = fileLoc)

#Read reference files
ref <- read_reference(sample.table, system = "bio-rad",
                      file.location = fileLoc)

#Read samples files
samp <- read_sample(sample.table, system = "bio-rad",
                    file.location = fileLoc)

#Reference DBSCAN clustering
dbref <- reference_dbscan(ref, sample.table, save.template = FALSE)

#Predict position of clusters centroid from reference DBSCAN results
cent <- centers_data(samp, sample.table,dbref)

#Fuzzy c-means clustering
cmclus <- cmeans_clus(cent)

#Rain classification.
rainclus <- rain_reclus(cmclus)

#Quantification
quantcm <- target_quant(cmclus, sample.table)
quant <- target_quant(rainclus, sample.table)