run_interptimes: Interpolate time-series phenotypes in 'R/qtl' CSV file.
In gact/shmootl: QTL Analysis Utilities for Yeast
Description
Usage
Arguments
Author(s)
See Also
View source: R/run_interptimes.R
Description
Read data in an R/qtl cross CSV file. If the input cross has
time-series phenotypes, interpolate phenotype values in any gaps in the
time series, then write the resulting cross to the output file.
Usage
1
run_interptimes(datafile = NA_character_, tol = 1e-05)
Arguments
datafile
cross CSV file [required]
tol
time-step equality tolerance
Author(s)
Yue Hu
See Also
Other pipeline functions: run_annoqtl,
run_digest, run_estimap,
run_makecross, run_makegeno,
run_prep, run_pullmap,
run_pushmap, run_recode,
run_report, run_scanone,
run_scantwo
gact/shmootl documentation built on Nov. 11, 2021, 6:23 p.m.
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Description Usage Arguments Author(s) See Also
View source: R/run_interptimes.R
Description
Read data in an R/qtl cross CSV file. If the input cross has
time-series phenotypes, interpolate phenotype values in any gaps in the
time series, then write the resulting cross to the output file.
Usage
1 | run_interptimes(datafile = NA_character_, tol = 1e-05)
|
Arguments
datafile |
cross CSV file [required] |
tol |
time-step equality tolerance |
Author(s)
Yue Hu
See Also
Other pipeline functions: run_annoqtl,
run_digest, run_estimap,
run_makecross, run_makegeno,
run_prep, run_pullmap,
run_pushmap, run_recode,
run_report, run_scanone,
run_scantwo
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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