dPCP {dPCP}

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.

color.blind

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")