Description Usage Arguments Details
View source: R/variants_power.R
Compute sensitivity and specificity for the a set of variants with respect to some truth sets
1 2 3 4 | variants_power(variant_files, variant_files_initial, down_label = NA,
truth_set = NA, caller, gene_expression = NA, normal_variants,
exon_ranges, homop_ranges, RNAedit_ranges, repeats_ranges, ncbi,
flag_patterns, path_to_gatk_coverage, TCGA = FALSE)
|
variant_files |
character vector containing the paths to all the tab delimited files of variants from the downsampled run. See details. |
variant_files_initial |
character vector containing the paths to all the tab delimited files of variants from the initial run with deeply sequenced RNA-Seq samples. See details. |
down_label |
character. Any label to be assigned to the current run |
truth_set |
external truth set |
caller |
one of 'varscan', 'mutect' or 'vardict' |
gene_expression |
if available, 'rds' objects with raw gene expression data where rows are genes and columns are samples |
normal_variants |
link to panel of normal file parsed with 'samplepower::parse_pon' |
exon_ranges |
GRanges object with exon boundaries relative to the reference genome used |
homop_ranges |
GRanges object with homopolymers regions of more than 5bp relative to the reference genome used |
RNAedit_ranges |
GRanges object with RNA editing sites relative to the reference genome used |
repeats_ranges |
GRanges object with repetitive regions of the reference genome used |
ncbi |
NCBI annotation dataframe including at least the columns 'GeneID' and 'Symbol' |
flag_patterns |
dataframe containing the flags to assign to variants. THIS NEEDS TO BE SET AS INTERNAL TO THE PACKAGE |
path_to_gatk_coverage |
path to file where the GATK 'DepthOfCoverage' output is saved |
TCGA |
logical. If TRUE variants will be macthed with truth sets excluding transcript information |
The files whose links are recorded in 'variant_files_initial' and 'variant_files' are the ouput files obtained with the 'call_variants.R' function from the functions in https://github.com/annaquaglieri16/RNA-seq-variant-calling#panel-of-normals-pon. The VCF output from every callers are standardised to make the results easily comparable across callers.
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