problem.joint.predict.job: problem joint predict job
In tdhock/PeakSegPipeline: Genome-Wide Peak Prediction Using Supervised Learning and Optimal Segmentation
Description
Usage
Arguments
Value
Author(s)
Description
Compute all joint peak predictions for the joint problems listed
in jobProblems.bed, in parallel over problems using
psp_lapply.
Usage
1
2
3
problem.joint.predict.job(job.dir,
verbose = getOption("PeakSegPipeline.verbose",
1))
Arguments
job.dir
project/jobs/jobID
verbose
Value
data.table of predicted peaks, one row for each job, same columns
as from problem.joint.predict.
Author(s)
Toby Dylan Hocking
tdhock/PeakSegPipeline documentation built on March 3, 2020, 1:35 a.m.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Author(s)
Description
Compute all joint peak predictions for the joint problems listed
in jobProblems.bed, in parallel over problems using
psp_lapply.
Usage
1 2 3 | problem.joint.predict.job(job.dir,
verbose = getOption("PeakSegPipeline.verbose",
1))
|
Arguments
job.dir |
project/jobs/jobID |
verbose |
Value
data.table of predicted peaks, one row for each job, same columns
as from problem.joint.predict.
Author(s)
Toby Dylan Hocking
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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