read.csp.profile: likeLTD::read.csp.profile

Description Usage Arguments Details Value See Also Examples

View source: R/hypothesis.R

Description

Reads the Crime Scene Profile from a CSV file.

Usage

1

Arguments

path

Path to the crime scene profile.

Details

The input is a file in the CSV format (comma-separated values). It should have the following form:

Stain Profiling system Plate/Run Allelic/Uncertain Locus Locus ...
IGNORED IGNORED IGNORED Allelic "13,14,15" "16,16" ...
IGNORED IGNORED IGNORED Uncertain "17.2" ...

Columns are separted by commas (not present in the table above). The first line, containing the name of the columns need be present. The first three columns are ignored for the purpose of the likeLTD package. They are present (and expected) merely for convenience. The fourth column indicates whether a line contains certain or uncertain alleles. "Uncertain" implies the latter, anything else implies the former. Beware of the capitalization. The next columns are for loci. "Locus" should be replaced with the actual locus name in the first line. Other lines should contain the comma-separated names of the alleles present in the CSP, within quotation marks. Entries can be empty. The lines labeled "Uncertain" are ignored by this function.

Value

A matrix where columns are loci and rows are replicates. Each element is a vector of character, and each character is the name of an allele certainly present in the CSP for that loci and replicate. For simplicity, loci for which all entries are NA are removed.

See Also

read.unc.profile, read.known.profiles

Examples

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## Not run: 
# datapath to example files
datapath = file.path(system.file("extdata", package="likeLTD"),"hammer")

# File paths and case name for allele report
admin = pack.admin.input(
            cspFile = file.path(datapath, 'hammer-CSP.csv'),
            refFile = file.path(datapath, 'hammer-reference.csv'),
            caseName = "hammer",
	    kit= "SGMplus"
             )

# get CSP
read.csp.profile(admin$cspFile)

## End(Not run)

likeLTD documentation built on May 1, 2019, 7:58 p.m.