CallPA: Calls Presence/Absence for a given input file

In dsherma7/PolyploidDosageCalling: Calls the Dosage From Tetraploid qPCR Data (CT/RQ Values)

Description

Uses a clustering algorithm to cluster the 3 categories: Positive, Negative, NTC on the file provided. Requires known control values as specified in the Control.File.

Usage

CallPA(File, Control.File = "Controls.csv", Output.Dir = "Output",
  Directory = NULL, sheet = "Results", Console = F,
  Output.File = "PA.csv")

Arguments

File	Name of the file containing the raw data from a Quant Studio qPCR run. The column Clone-plant_ID must be added.
Control.File	Name of the file containing the controls. Must contain 2 columns, Name and Presence, with Name matching the values in Clone-Plant_ID for control samples. (Default = Controls.csv)
Directory	The directory containing the necessary files. Default to NULL which will use current directory.
sheet	The name in File where Clone-Plant_ID and RQ values are stored. Default = "Results".
Console	Should plots be printed to the console? Default is False which prints the plots to Output.Dir.
Output.File	The name of the output file containing the final dosage calls. Defaults to Dosage.csv.

Value

A dataset containing the dosage calls of each of the methods and a final determination of the dosage and likelihood.

See Also

CallDosage for calling the dosage of provided data

Examples

# Obtain the appropriate Control and Raw Data files. You can find these in the
# data-raw/ folder of the Quadrophenia package files.They should match the data below.

# A 41 line header
# Followed by the output of QuantStudio's Results sheet
# Note that Clone-plant_ID must be added manually to this file

require(Quadrophenia)
RawData.Assay2[1:41,1] # Header
RawData.Assay2[42,]    # Columns of data

# The controls file has two columns: Clone-plant_ID and Presence. Clone-plant_ID must
# match the Clone-plant_ID columns for the associated controls in the raw data file.

head(ControlsAssay2)

# Then run CallPA() with these files as inputs

output = CallPA(File='RawData.Assay2.xls',Control.File='ControlsAssay2.csv')

# The output directory Output/ should contain 1 .csv file and a Plots/ directory.
# The Plots/ directory contains one plot showing the clustering of Positive, Negative,
# and Undetermined calls for the expression of the target & reference assays.

head(output)

## Other ways to run CallPA()
# You could also specifiy an output file or a directory to look for the raw data files

dir.create('Files/')
file.copy(c('RawData.Assay2.xls','ControlsAssay2.csv'),'Files/')
output = CallPA(File='RawData.Assay2.xls',
                Control.File='ControlsAssay2.csv',
                Directory='Files/',Output.Dir='NewOutput')

# Or specify the files in Files/ wihout specifying the directory. You can
# also change the name of the output file to something more informative.

output = CallPA(File='Files/RawData.Assay2.xls',
                Control.File='Files/ControlsAssay2.csv',
                Output.Dir='ThirdOutput',
                Output.File='ThirdOutputPA.csv')

# Duplicates will automatically be renamed to avoid conflicts

output = CallPA(File='Files/RawData.Assay2.xls',
                Control.File='Files/ControlsAssay2.csv',
                Output.Dir='ThirdOutput',
                Output.File='ThirdOutputPA.csv')

# Clean up the test files
unlink(c('Files','Output','ThirdOutput'),recursive=T)

dsherma7/PolyploidDosageCalling documentation built on May 23, 2019, 6:06 p.m.