Plot Marginals of Variant Allele Frequency (VAF)
Source:R/plot_vaf_marginals.R
plot_VAF_marginals.RdThis function generates scatter plots showing the marginal distributions of Variant Allele Frequency (VAF) for pairs of samples on a specific chromosome.
Usage
plot_VAF_marginals(
seq_result,
chromosomes = NULL,
samples = NULL,
labels = NULL,
cuts = c(0, 1)
)Arguments
- seq_result
A data frame containing sequencing results in wide format.
- samples
A character vector specifying the sample names to include in the plot. (default: NULL. It includes all samples except the "normal_sample").
- cuts
A numeric vector specifying the range of VAF values to include in the plot (default:
c(0, 1)).- chromosome
A character specifying the chromosome to analyze (default: all the chromosomes in
seq_res).- colour_by
A character indicating whether to color the scatter points by "causes" or "classes" (default: "causes").
Examples
# set the seed of the random number generator
set.seed(0)
sim <- SpatialSimulation()
sim$add_mutant(name = "A",
growth_rates = 0.1,
death_rates = 0.0)
sim$place_cell("A", 500, 500)
sim$run_up_to_time(100)
#>
[████████████████████████████████████████] 100% [00m:00s] Saving snapshot
# sampling tissue
n_w <- n_h <- 10
ncells <- 0.8 * n_w * n_h
bbox <- sim$search_sample(c("A" = ncells), n_w, n_h)
sim$sample_cells("SampleA", bbox$lower_corner, bbox$upper_corner)
# adding second mutant
sim$add_mutant(name = "B",
growth_rates = 0.3,
death_rates = 0.0)
sim$mutate_progeny(sim$choose_cell_in("A"), "B")
sim$run_up_to_time(300)
#>
[████████████████████████████████████████] 100% [00m:00s] Saving snapshot
# sampling tissue again
bbox <- sim$search_sample(c("B" = ncells), n_w, n_h)
sim$sample_cells("SampleB", bbox$lower_corner, bbox$upper_corner)
forest <- sim$get_samples_forest()
# placing mutations
m_engine <- MutationEngine(setup_code = "demo")
#> Downloading reference genome...
#> Reference genome downloaded
#> Decompressing reference file...done
#> Downloading SBS file...
#> SBS file downloaded
#> Downloading indel file...
#> indel file downloaded
#> Downloading driver mutation file...
#> Driver mutation file downloaded
#> Downloading passenger CNAs file...
#> Passenger CNAs file downloaded
#> Downloading germline mutations...
#> Germline mutations downloaded
#> Building context index...
#>
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[████████████████████████████████████████] 100% [00m:02s] Context index built
#>
[█---------------------------------------] 0% [00m:00s] Saving context index
[████████████████████████████████████████] 100% [00m:00s] Context index saved
#> done
#> Building repeated sequence index...
#>
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#>
[█---------------------------------------] 0% [00m:00s] Saving RS index
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done
#>
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#>
[█---------------------------------------] 0% [00m:00s] Loading germline
[████████████████████████████████████████] 100% [00m:00s] Germline loaded
#>
[█---------------------------------------] 0% [00m:00s] Saving germline
[████████████████████████████████████████] 100% [00m:00s] Germline saved
m_engine$add_mutant(mutant_name="A", passenger_rates=c(SNV=5e-8))
#>
[█---------------------------------------] 0% [00m:00s] Retrieving "A" SNVs
[████████████████████████████████████████] 100% [00m:00s] "A" SNVs retrieved
m_engine$add_mutant(mutant_name="B", passenger_rates=c(SNV=5e-9))
#>
[█---------------------------------------] 0% [00m:00s] Retrieving "B" SNVs
[████████████████████████████████████████] 100% [00m:00s] "B" SNVs retrieved
m_engine$add_exposure(c(SBS1 = 0.2, SBS5 = 0.8))
phylo_forest <- m_engine$place_mutations(forest, 10, 10)
#>
[█---------------------------------------] 0% [00m:00s] Placing mutations
[████████████████████████████████████████] 100% [00m:00s] Mutations placed
# simulating sequencing without the normal sample
seq_results <- simulate_seq(phylo_forest, coverage = 10, write_SAM = F,
with_normal_sample = FALSE)
#>
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library(dplyr)
# filter germinal mutations
f_seq <- seq_results$mutations %>% filter(classes!="germinal")
# plotting the VAR marginals
plot_VAF_marginals(f_seq)
#> [[1]]
#>
# plotting the VAF marginals and labelling it
plot_VAF_marginals(f_seq, labels = f_seq["causes"])
#> [[1]]
#>
# deleting the mutation engine directory
unlink('demo', recursive = T)