R Under development (unstable) (2025-04-23 r88174 ucrt) -- "Unsuffered Consequences"
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> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
> 
> library(testthat)
> library(colocboost)
> 
> test_check("colocboost")
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Extracting colocalization results with cos_npc_cutoff = 0.2 and npc_outcome_cutoff = 0.1.
Keep only CoS with cos_npc >= 0.2. For each CoS, keep the outcomes configurations that the npc_outcome >= 0.1.
Validating input data.
Validating input data.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for outcome 2 converged after 50 iterations!
Gradient boosting for outcome 1 converged after 65 iterations!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for outcome 1 converged after 4 iterations!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for outcome 1 converged after 2 iterations!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
No ambiguous colocalization events!
There exists the ambiguous colocalization events from trait-specific effects. Extracting!
There are 1 ambiguous trait-specific effects.
There exists the ambiguous colocalization events from trait-specific effects. Extracting!
There are 1 ambiguous trait-specific effects.
There exists the ambiguous colocalization events from trait-specific effects. Extracting!
There are 1 ambiguous trait-specific effects.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Extracting colocalization results with cos_npc_cutoff = 0.5 and npc_outcome_cutoff = 0.2.
Keep only CoS with cos_npc >= 0.5. For each CoS, keep the outcomes configurations that the npc_outcome >= 0.2.
Extracting colocalization results with cos_npc_cutoff = 0.8 and npc_outcome_cutoff = 0.2.
Keep only CoS with cos_npc >= 0.8. For each CoS, keep the outcomes configurations that the npc_outcome >= 0.2.
Extracting colocalization results with pvalue_cutoff = 0.05, cos_npc_cutoff = 0.5, and npc_outcome_cutoff = 0.2.
Keep only CoS with cos_npc >= 0.5. For each CoS, keep the outcomes configurations that pvalue of variants for the outcome < 0.05 and npc_outcome >0.2.
There exists the ambiguous colocalization events from trait-specific effects. Extracting!
There are 1 ambiguous trait-specific effects.
No ambiguous colocalization events!
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
There exists the ambiguous colocalization events from trait-specific effects. Extracting!
There are 1 ambiguous trait-specific effects.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for outcome 1 converged after 109 iterations!
Gradient boosting for outcome 3 converged after 112 iterations!
Gradient boosting for outcome 2 converged after 115 iterations!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for outcome 1 converged after 109 iterations!
Gradient boosting for outcome 3 converged after 112 iterations!
Gradient boosting for outcome 2 converged after 115 iterations!
Performing inference on colocalization events.
No ambiguous colocalization events!
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for focal outcome 4 converged after 68 iterations!
Gradient boosting for outcome 2, 3 converged after 178 iterations!
Gradient boosting for outcome 1 converged after 185 iterations!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for focal outcome 4 converged after 68 iterations!
Gradient boosting for outcome 2, 3 converged after 178 iterations!
Gradient boosting for outcome 1 converged after 185 iterations!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for outcome 1 converged after 70 iterations!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for focal outcome 4 converged after 68 iterations!
Gradient boosting for outcome 2, 3 converged after 178 iterations!
Gradient boosting for outcome 1 converged after 185 iterations!
Performing inference on colocalization events.
Show all CoSs to uncolocalized outcomes.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for focal outcome 4 converged after 68 iterations!
Gradient boosting for outcome 2, 3 converged after 178 iterations!
Gradient boosting for outcome 1 converged after 185 iterations!
Performing inference on colocalization events.
Show all CoSs to uncolocalized outcomes.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for focal outcome 4 converged after 68 iterations!
Gradient boosting for outcome 2, 3 converged after 178 iterations!
Gradient boosting for outcome 1 converged after 185 iterations!
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Gradient boosting for focal outcome 4 converged after 68 iterations!
Gradient boosting for outcome 2, 3 converged after 178 iterations!
Gradient boosting for outcome 1 converged after 185 iterations!
Performing inference on colocalization events.
Extracting colocalization results with cos_npc_cutoff = 0.5 and npc_outcome_cutoff = 0.2.
Keep only CoS with cos_npc >= 0.5. For each CoS, keep the outcomes configurations that the npc_outcome >= 0.2.
Show all CoSs to uncolocalized outcomes.
Extracting colocalization results with cos_npc_cutoff = 0.7 and npc_outcome_cutoff = 0.3.
Keep only CoS with cos_npc >= 0.7. For each CoS, keep the outcomes configurations that the npc_outcome >= 0.3.
Show all CoSs to uncolocalized outcomes.
Extracting colocalization results with cos_npc_cutoff = 0.9 and npc_outcome_cutoff = 0.5.
Keep only CoS with cos_npc >= 0.9. For each CoS, keep the outcomes configurations that the npc_outcome >= 0.5.
Show all CoSs to uncolocalized outcomes.
Extracting colocalization results with cos_npc_cutoff = 1 and npc_outcome_cutoff = 0.5.
Keep only CoS with cos_npc >= 1. For each CoS, keep the outcomes configurations that the npc_outcome >= 0.5.
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
Extracting colocalization results with cos_npc_cutoff = 0.5 and npc_outcome_cutoff = 1.
Keep only CoS with cos_npc >= 0.5. For each CoS, keep the outcomes configurations that the npc_outcome >= 1.
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
Extracting colocalization results with cos_npc_cutoff = 1 and npc_outcome_cutoff = 1.
Keep only CoS with cos_npc >= 1. For each CoS, keep the outcomes configurations that the npc_outcome >= 1.
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
There is no colocalization in this region!. Showing margianl for all outcomes!
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Running ColocBoost with assumption of one causal per outcome per region!
Performing inference on colocalization events.
Validating input data.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
Validating input data.
Starting gradient boosting algorithm.
Performing inference on colocalization events.
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 339 ]
> 
> proc.time()
   user  system elapsed 
  18.34    1.40   19.75