mtree
tree.print.mtree.Rd
Print a mtree
tree.
# S3 method for mtree print(x, ...)
x | A |
---|---|
... | Extra S3 parameters |
Nothing
Print a summary for a mtree
object, which includes a
shell-frinedly layout and other information.
data(mtree_input) x = mtrees( mtree_input$binary_clusters, mtree_input$drivers, mtree_input$samples, mtree_input$patient, mtree_input$sspace.cutoff, mtree_input$n.sampling, mtree_input$store.max )#> [ mtree ~ generate mutation trees for PD9193 ] #> Sampler : 10000 (cutoff), 5000 (sampling), 100 (max store) #> Suppes' conditions : >= #> # A tibble: 4 x 14 #> Misc patientID cluster is.driver is.clonal PD9193d PD9193e PD9193f PD9193g #> <chr> <chr> <chr> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> #> 1 cuto… PD9193 2 FALSE FALSE 1 1 1 0 #> 2 cuto… PD9193 3 TRUE FALSE 1 0 0 0 #> 3 cuto… PD9193 1 TRUE TRUE 1 1 1 1 #> 4 cuto… PD9193 4 TRUE FALSE 1 0 1 1 #> # … with 5 more variables: PD9193h <dbl>, PD9193i <dbl>, PD9193j <dbl>, #> # PD9193k <dbl>, nMuts <dbl> #> #> ✔ Structures 3 - search is exahustive #> ✔ Trees with non-zero sscore 3 storing 3 #>#> [ mtree - mtree rank 1/3 for PD9193 ] #> #> # A tibble: 4 x 14 #> Misc patientID cluster is.driver is.clonal PD9193d PD9193e PD9193f PD9193g #> <chr> <chr> <chr> <lgl> <lgl> <dbl> <dbl> <dbl> <dbl> #> 1 cuto… PD9193 2 FALSE FALSE 1 1 1 0 #> 2 cuto… PD9193 3 TRUE FALSE 1 0 0 0 #> 3 cuto… PD9193 1 TRUE TRUE 1 1 1 1 #> 4 cuto… PD9193 4 TRUE FALSE 1 0 1 1 #> # … with 5 more variables: PD9193h <dbl>, PD9193i <dbl>, PD9193j <dbl>, #> # PD9193k <dbl>, nMuts <dbl> #> #> Tree shape (drivers annotated) #> #> \-GL #> \-1 [PD9193k] :: GATA3 #> |-4 :: +8q, -8p #> | \-3 :: SMARCA4 #> \-2 #> #> Information transfer #> #> +8q ---> SMARCA4 #> -8p ---> SMARCA4 #> GL ---> GATA3 #> GATA3 ---> +8q #> GATA3 ---> -8p #> #> Tree score 0.000697748027942915 #>