TINC is a package to estimate Tumour-in-Normal (TIN) and Tumour-in-Tumour (TIT) scores for a matched tumour-normal assay (ideally, a whole-genome one).
TINC takes as input mutation data, with read counts reported for both the tumour and the matched normal.
Somatic mutations. Input mutations should report the following information:
chr, from, to, ref
and alt
n_ref_count and
n_alt_count.t_ref_count and t_tot_count.Example input mutations are shown below.
Copy number segments. Optionally, allele-specific copy number segments can also be used These can be extremely important if the sample has high levels of aneuploidy, and we do suggest to use those in such cases.
Copy number segments data must follow the formats from the CNAqc package:
chr,
from and to
Major and
minor alleles
# devtools::install_github("caravagnalab/CNAqc")
require(CNAqc)
#> Loading required package: CNAqc
# This is the format
CNAqc::example_dataset_CNAqc$cna %>% print
#> # A tibble: 267 × 7
#> chr from to length covRatio Major minor
#> <chr> <int> <int> <int> <dbl> <dbl> <dbl>
#> 1 chr1 840009 1689987 849979 1.19 3 2
#> 2 chr1 1689988 1815015 125028 1.26 3 2
#> 3 chr1 1815016 9799969 7984954 1.19 3 2
#> 4 chr1 10479910 12079917 1600008 1.19 3 2
#> 5 chr1 12079917 12154980 75064 1.24 3 2
#> 6 chr1 12154981 12839977 684997 1.19 3 2
#> 7 chr1 13780016 17790026 4010011 1.19 3 2
#> 8 chr1 17849962 21080067 3230106 1.19 3 2
#> 9 chr1 21080068 21559998 479931 1.26 3 2
#> 10 chr1 21559998 24830001 3270004 1.19 3 2
#> # ℹ 257 more rows