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Hi,
Thank you for amazing works.
I'm encountering an issue while attempting to generate a knockdown model and would appreciate some help. I have successfully followed the tutorial to generate model_common. However, I am facing the following error when trying to generate model_ko:
Error in `tibble()`:
! Tibble columns must have compatible sizes.
• Size 500: Existing data.
• Size 100: Column at position 6.
ℹ Only values of size one are recycled.
I suspect the issue may arise from generating a more complex tf_network where I did not use the default nrow(backbone$module_info). Here is the code I used to generate model_common:
set.seed(42)
backbone <- backbone_bifurcating()
config <-
initialise_model(
backbone = backbone,
num_cells = 5000,
num_tfs = 100,
num_targets = 500,
num_hks = 100,
verbose = FALSE,
download_cache_dir = tools::R_user_dir("dyngen", "data"),
simulation_params = simulation_default(
total_time = 1000,
census_interval = 2,
ssa_algorithm = ssa_etl(tau = 300/3600),
experiment_params = simulation_type_wild_type(num_simulations = 100)
)
)
model_common <-
config %>%
generate_tf_network() %>%
generate_feature_network() %>%
generate_kinetics() %>%
generate_gold_standard()
Then, the code to generate model_ko is as follows:
plot_backbone_modulenet(model_common)
b3_genes <- model_common$feature_info %>% filter(module_id == "B3") %>% pull(feature_id)
model_ko <- model_common
model_ko$simulation_params$experiment_params <- simulation_type_knockdown(
num_simulations = 100L,
timepoint = 0.2,
genes = b3_genes,
num_genes = length(b3_genes),
multiplier = 0
)
I suspect the issue may be related to not using the default number of rows when generating tf_network. Is there a way to resolve this issue, or how should I correctly generate a more complex tf_network?
Thank you!
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