identify_vcf_file {Uniquorn} | R Documentation

## 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
    )

[Package Uniquorn version 2.4.0 Index]