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With end_n == 2
library(dyno) library(tidyverse) data("fibroblast_reprogramming_treutlein") dataset <- wrap_expression( counts = fibroblast_reprogramming_treutlein$counts, expression = fibroblast_reprogramming_treutlein$expression ) model <- infer_trajectory(dataset = dataset %>% add_prior_information(end_n = 2), method = ti_grandprix(), verbose = TRUE) model$milestone_network
# A tibble: 2 x 4 from to length directed <chr> <chr> <dbl> <lgl> 1 milestone_begin split_0_1 1 TRUE 2 milestone_begin split_0_2 1 TRUE
With end_n == 3
model <- infer_trajectory(dataset = dataset %>% add_prior_information(end_n = 2), method = ti_grandprix(), verbose = TRUE) model$milestone_network
# A tibble: 6 x 4 from to length directed <chr> <chr> <dbl> <lgl> 1 milestone_begin split_0_1 1 TRUE 2 milestone_begin split_0_2 1 TRUE 3 milestone_begin split_1_1 1 TRUE 4 milestone_begin split_1_2 1 TRUE 5 milestone_begin split_2_1 1 TRUE 6 milestone_begin split_2_2 1 TRUE
Also, when end_n == 1, a more useful error message should be generated (See dynverse/dyno#30)
The text was updated successfully, but these errors were encountered:
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With end_n == 2
With end_n == 3
Also, when end_n == 1, a more useful error message should be generated (See dynverse/dyno#30)
The text was updated successfully, but these errors were encountered: