cal_betas: calculates betacoefficients from explained variances
In askieslinger/MRTool: Simulating Data for Mendelian Randomization Scenarios Based on Genotype Data
Description
Usage
Arguments
Value
View source: R/preprocessing.R
Description
For examples see vignette browseVignettes('MRTool')
Usage
1
cal_betas(pves, maf, gy_direct = T)
Arguments
pves
a named list of parameters and percentages of variance explained for each one.
If multiple snps, each param is a list of snp-vectors, each vector the scenarios for this snp
maf
a named list of maf for every snp
gy_direct
should there be a direct effect of G on Y. default true. does not need to be changed.
Value
a list of two data.tables. a data.table containing all valid combinations
of coefficients, one row is one snp in one scenario. A data.table with the adjusted combinations
of percentages of variance explained
askieslinger/MRTool documentation built on April 29, 2020, 12:02 p.m.
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Description Usage Arguments Value
View source: R/preprocessing.R
Description
For examples see vignette browseVignettes('MRTool')
Usage
1 | cal_betas(pves, maf, gy_direct = T)
|
Arguments
pves |
a named list of parameters and percentages of variance explained for each one. If multiple snps, each param is a list of snp-vectors, each vector the scenarios for this snp |
maf |
a named list of maf for every snp |
gy_direct |
should there be a direct effect of G on Y. default true. does not need to be changed. |
Value
a list of two data.tables. a data.table containing all valid combinations of coefficients, one row is one snp in one scenario. A data.table with the adjusted combinations of percentages of variance explained
R Package Documentation
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