Harmonise exposure and outcome for multivariable MR

mv_harmonise_data(exposure_dat, outcome_dat, harmonise_strictness = 2)

Arguments

exposure_dat

Output from mv_extract_exposures.

outcome_dat

Output from extract_outcome_data(exposure_dat$SNP, id_output).

harmonise_strictness

See the action option of harmonise_data. The default is 2.

Value

List of vectors and matrices required for mv analysis.

exposure_beta

a matrix of beta coefficients, in which rows correspond to SNPs and columns correspond to exposures.

exposure_se

is the same as exposure_beta, but for standard errors.

exposure_pval

the same as exposure_beta, but for p-values.

expname

A data frame with two variables, id.exposure and exposure which are character strings.

outcome_beta

an array of effects for the outcome, corresponding to the SNPs in exposure_beta.

outcome_se

an array of standard errors for the outcome.

outcome_pval

an array of p-values for the outcome.

outname

A data frame with two variables, id.outcome and outcome which are character strings.