Read FACETS CNA calls
facets.RdReads the variant calls from FACETS CNA caller
Arguments
- path
Can be either:
path to a single file, sample ID can be passed using sample_id argument
vector of file paths, element names will be used as sample IDs
directory containing multiple FACETS .csv files, sample IDs will be guessed from the file names
- sample_id
Sample ID, used with path is a single file
- chrom_convention
UCSC/NCBI/keep
Examples
library(readthis)
file1 <- system.file("extdata", "FACETS", "S1.csv", package = "readthis")
read_facets_cnas(file1)
#> # A tibble: 64 × 18
#> sample_id chrom start end total_cn major_cn minor_cn log_ratio seg
#> <chr> <chr> <int> <int> <int> <int> <int> <dbl> <dbl>
#> 1 /home/runner/… chr1 1.75e4 1.00e7 1 1 0 -0.261 1
#> 2 /home/runner/… chr1 1.00e7 1.49e8 2 1 1 -0.0364 2
#> 3 /home/runner/… chr1 1.49e8 2.49e8 3 2 1 0.130 3
#> 4 /home/runner/… chr2 4.56e4 9.50e7 2 1 1 -0.0417 4
#> 5 /home/runner/… chr2 9.51e7 9.85e7 3 NA NA 0.122 5
#> 6 /home/runner/… chr2 9.85e7 1.00e8 2 NA NA 0.0293 6
#> 7 /home/runner/… chr2 1.00e8 1.12e8 1 1 0 -0.256 7
#> 8 /home/runner/… chr2 1.12e8 2.09e8 2 1 1 -0.0440 8
#> 9 /home/runner/… chr2 2.10e8 2.18e8 1 1 0 -0.248 9
#> 10 /home/runner/… chr2 2.18e8 2.37e8 2 1 1 -0.0576 10
#> # ℹ 54 more rows
#> # ℹ 9 more variables: num.mark <dbl>, nhet <dbl>, mafR <dbl>, segclust <dbl>,
#> # cnlr.median.clust <dbl>, mafR.clust <dbl>, cf.em <dbl>, Purity <dbl>,
#> # Ploidy <dbl>
file2 <- system.file("extdata", "FACETS", "S2.csv", package = "readthis")
files <- c(S1 = file1, S2 = file2)
read_facets_cnas(files)
#> # A tibble: 128 × 18
#> sample_id chrom start end total_cn major_cn minor_cn log_ratio seg
#> <chr> <chr> <int> <int> <int> <int> <int> <dbl> <dbl>
#> 1 S1 chr1 17500 1.00e7 1 1 0 -0.261 1
#> 2 S1 chr1 10008200 1.49e8 2 1 1 -0.0364 2
#> 3 S1 chr1 148953300 2.49e8 3 2 1 0.130 3
#> 4 S1 chr2 45600 9.50e7 2 1 1 -0.0417 4
#> 5 S1 chr2 95053400 9.85e7 3 NA NA 0.122 5
#> 6 S1 chr2 98538000 1.00e8 2 NA NA 0.0293 6
#> 7 S1 chr2 100321500 1.12e8 1 1 0 -0.256 7
#> 8 S1 chr2 112389300 2.09e8 2 1 1 -0.0440 8
#> 9 S1 chr2 209653415 2.18e8 1 1 0 -0.248 9
#> 10 S1 chr2 218385300 2.37e8 2 1 1 -0.0576 10
#> # ℹ 118 more rows
#> # ℹ 9 more variables: num.mark <dbl>, nhet <dbl>, mafR <dbl>, segclust <dbl>,
#> # cnlr.median.clust <dbl>, mafR.clust <dbl>, cf.em <dbl>, Purity <dbl>,
#> # Ploidy <dbl>
dir <- system.file("extdata", "FACETS", package = "readthis")
read_facets_cnas(dir)
#> # A tibble: 128 × 18
#> sample_id chrom start end total_cn major_cn minor_cn log_ratio seg
#> <chr> <chr> <int> <int> <int> <int> <int> <dbl> <dbl>
#> 1 S1 chr1 17500 1.00e7 1 1 0 -0.261 1
#> 2 S1 chr1 10008200 1.49e8 2 1 1 -0.0364 2
#> 3 S1 chr1 148953300 2.49e8 3 2 1 0.130 3
#> 4 S1 chr2 45600 9.50e7 2 1 1 -0.0417 4
#> 5 S1 chr2 95053400 9.85e7 3 NA NA 0.122 5
#> 6 S1 chr2 98538000 1.00e8 2 NA NA 0.0293 6
#> 7 S1 chr2 100321500 1.12e8 1 1 0 -0.256 7
#> 8 S1 chr2 112389300 2.09e8 2 1 1 -0.0440 8
#> 9 S1 chr2 209653415 2.18e8 1 1 0 -0.248 9
#> 10 S1 chr2 218385300 2.37e8 2 1 1 -0.0576 10
#> # ℹ 118 more rows
#> # ℹ 9 more variables: num.mark <dbl>, nhet <dbl>, mafR <dbl>, segclust <dbl>,
#> # cnlr.median.clust <dbl>, mafR.clust <dbl>, cf.em <dbl>, Purity <dbl>,
#> # Ploidy <dbl>