> Reference > > dynwrap :: Creating a trajectory > Create a trajectory given its branch network and the pseudotime of the cells on one of the branches

Create a trajectory given its branch network and the pseudotime of the cells on one of the branches

add_branch_trajectory(dataset, branch_network, branches,
  branch_progressions, ...)

Arguments

dataset	A dataset created by `wrap_data()` or `wrap_expression()`
branch_network	The network between branches Type: Data frame(from = charactor, to = character)
branches	The length and directedness of the branches Type: Data frame(branch_id = character, length = numeric, directed = logical)
branch_progressions	Specifies the progression of a cell along a transition in the branch network. Type: Data frame(cell_id = character, branch_id = character, percentage = numeric).
...	extra information to be stored in the trajectory

Value

The trajectory

Examples

library(tibble)
dataset <- wrap_data(cell_ids = letters)

branch_network <- tibble(from = c("A", "A"), to = c("B", "C"))
branch_network
#> # A tibble: 2 x 2
#>   from  to   
#>   <chr> <chr>
#> 1 A     B    
#> 2 A     C    
branches <- tibble(branch_id = c("A", "B", "C"), length = 1, directed = TRUE)
branches
#> # A tibble: 3 x 3
#>   branch_id length directed
#>   <chr>      <dbl> <lgl>   
#> 1 A              1 TRUE    
#> 2 B              1 TRUE    
#> 3 C              1 TRUE    
branch_progressions <- tibble(
  cell_id = dataset$cell_ids,
  branch_id = sample(branches$branch_id, length(dataset$cell_ids), replace = TRUE),
  percentage = runif(length(dataset$cell_ids))
)
branch_progressions
#> # A tibble: 26 x 3
#>    cell_id branch_id percentage
#>    <chr>   <chr>          <dbl>
#>  1 a       B             0.0763
#>  2 b       C             0.343 
#>  3 c       A             0.881 
#>  4 d       B             0.546 
#>  5 e       A             0.208 
#>  6 f       A             0.812 
#>  7 g       B             0.605 
#>  8 h       C             0.741 
#>  9 i       A             0.755 
#> 10 j       C             0.389 
#> # … with 16 more rows
trajectory <- add_branch_trajectory(
  dataset,
  branch_network,
  branches,
  branch_progressions
)

# for plotting the result, install dynplot
dynplot::plot_graph(trajectory)
#> Coloring by milestone
#> Using milestone_percentages from trajectory