identify_vcf_file: identify_VCF_file

In RaikOtto/Younikorn: Identification of cancer cell lines based on their weighted mutational/ variational fingerprint

identify_VCF_file

Description

Identifies a cancer cell lines contained in a vcf file based on the pattern (start & length) of all contained mutations/ variations.

Usage

identify_vcf_file( 
    vcf_file,
    output_file,
    ref_gen,
    minimum_matching_mutations,
    mutational_weight_inclusion_threshold,
    write_xls,
    output_bed_file,
    top_hits_per_library,
    manual_identifier,
    verbose,
    p_value,
    confidence_score,
    n_threads,
    write_results
)

Arguments

vcf_file	Input vcf file. Only one sample column allowed.
output_file	Path of the output file. If blank, autogenerated as name of input file plus '_uniquorn_ident.tab' suffix.
ref_gen	Reference genome version. All training sets are associated with a reference genome version. Default: GRCH37
minimum_matching_mutations	The minimum amount of mutations that has to match between query and training sample for a positive prediction
mutational_weight_inclusion_threshold	Include only mutations with a weight of at least x. Range: 0.0 to 1.0. 1= unique to CL. ~0 = found in many CL samples.
write_xls	Create identification results additionally as xls file for easier reading
output_bed_file	If BED files for IGV visualization should be created for the Cancer Cell lines that pass the threshold
top_hits_per_library	Limit the number of significant similarities per library to n (default 3) many hits. Is particularrly used in contexts when heterogeneous query and reference CCLs are being compared.
manual_identifier	Manually enter a vector of CL name(s) whose bed files should be created, independently from them passing the detection threshold
verbose	Print additional information
p_value	Required p-value for identification. Note that if you set the confidence score, the confidence score overrides the p-value
confidence_score	Cutoff for positive prediction between 0 and 100. Calculated by transforming the p-value by -1 * log(p-value) Note that if you set the confidence score, the confidence score overrides the p-value
n_threads	Number of threads to be used
write_results	Write identification results to file

Details

identify_vcf_file parses the vcf file and predicts the identity of the sample

Value

R table with a statistic of the identification result

Examples

HT29_vcf_file = system.file("extdata/HT29.vcf", package = "Uniquorn");

identification = identify_vcf_file(
    vcf_file = HT29_vcf_file, 
    verbose = FALSE,
    write_results = FALSE
)

RaikOtto/Younikorn documentation built on Oct. 18, 2022, 1:21 a.m.