Getting the sampled cells CNAs

This method returns the CNAs of the sample cells.

Arguments

cell_id: The identifier of the cell whose CNAs are aimed (optional).

Value

A dataframe reporting cell_id, type ("A" for amplifications and "D" for deletions), chr, begin (i.e., the first CNA locus in the chromosome), end (i.e., last CNA locus in the chromosome), allele, src allele (the allele origin for amplifications, NA for deletions), and class (i.e., "driver", "passenger", "germinal" or "preneoplastic").

Details

This method builds a dataframe representing all the CNAs in the cells sampled during the simulation and represented by the leaves of the phylogenetic forest.

Examples

sim <- SpatialSimulation()

sim$add_mutant(name = "Clone_1",
               epigenetic_rates = c("+-" = 0.01, "-+" = 0.01),
               growth_rates = c("+" = 0.2, "-" = 0.08),
               death_rates = c("+" = 0.05, "-" = 0.01))
sim$place_cell("Clone_1+", 500, 500)
sim$run_up_to_size("Clone_1-", 1000)
#> 
 [████████████████████████████████████████] 100% [00m:00s] Saving snapshot                                        


sim$sample_cells("Sample_A", c(475, 475), c(525, 525))
sample_forest <- sim$get_samples_forest()

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...
#> 
 [█---------------------------------------] 0% [00m:00s] Processing chr. 22                                       

 [█████████████████-----------------------] 40% [00m:01s] Processing chr. 22                                      

 [██████████████████████████████----------] 73% [00m:02s] Processing chr. 22                                      

 [████████████████████████████████████████] 100% [00m:02s] Context index built                                    

#> 
 [█---------------------------------------] 0% [00m:00s] Saving context index                                     

 [████████████████████████████████████████] 100% [00m:00s] Context index saved                                    

#> done
#> Building repeated sequence index...
#> 
 [█---------------------------------------] 0% [00m:00s] Processing chr. 22                                       

 [█---------------------------------------] 0% [00m:00s] Processing chr. 22                                       

 [█---------------------------------------] 0% [00m:03s] Processing chr. 22                                       

 [█---------------------------------------] 0% [00m:04s] Processing chr. 22                                       

 [█---------------------------------------] 0% [00m:06s] Processing chr. 22                                       

 [█---------------------------------------] 0% [00m:07s] Processing chr. 22                                       

 [█---------------------------------------] 0% [00m:09s] Processing chr. 22                                       

 [█---------------------------------------] 0% [00m:12s] Processing chr. 22                                       

 [████████████████████████████████████████] 100% [00m:12s] RS index built                                         

#> 
 [█---------------------------------------] 0% [00m:00s] Saving RS index                                          

 [█---------------------------------------] 0% [00m:01s] Saving RS index                                          

 [███████████████████████████-------------] 65% [00m:02s] Saving RS index                                         
done
#> 
 [████████████████████████████████████████] 100% [00m:02s] RS index saved                                         

#> 
 [█---------------------------------------] 0% [00m:00s] Loading germline                                         

 [████████████████████████████████████████] 100% [00m:00s] Germline loaded                                        

#> 
 [█---------------------------------------] 0% [00m:00s] Saving germline                                          

 [████████████████████████████████████████] 100% [00m:00s] Germline saved                                         


m_engine$add_mutant("Clone_1", list("+" = c(SNV = 1e-7, indel = 1e-8),
                                    "-" = c(SNV = 3e-7, CNA = 1e-11)),
                    list(SNV("22", 10510210, "C", allele = 1),
                         CNA("D", "22", 5010000, 200000,
                                   allele = 1)))
#> 
 [█---------------------------------------] 0% [00m:00s] Retrieving "Clone_1" SNVs                                

 [█---------------------------------------] 0% [00m:00s] Found 22                                                 

 [█---------------------------------------] 0% [00m:00s] Reading 22                                               

 [█---------------------------------------] 0% [00m:01s] Reading 22                                               

 [████████████████████████████████████████] 100% [00m:01s] "Clone_1" SNVs retrieved                               


m_engine$add_exposure(c(ID1 = 1, SBS1 = 0.5, SBS2 = 0.5))

phylo_forest <- m_engine$place_mutations(sample_forest, 1, 1)
#> 
 [█---------------------------------------] 0% [00m:00s] Placing mutations                                        

 [████████████████████████████████████████] 98% [00m:01s] Placing mutations                                       

 [████████████████████████████████████████] 100% [00m:01s] Mutations placed                                       


mutations <- phylo_forest$get_sampled_cell_CNAs()

head(mutations)
#>   cell_id type chr   begin     end allele src.allele  class
#> 1     546    D  22 5010000 5209999      1         NA driver
#> 2    1285    D  22 5010000 5209999      1         NA driver
#> 3    1475    D  22 5010000 5209999      1         NA driver
#> 4    1775    D  22 5010000 5209999      1         NA driver
#> 5    1885    D  22 5010000 5209999      1         NA driver
#> 6    2131    D  22 5010000 5209999      1         NA driver

Arguments

Value

Details

See also

Examples