MRAPSS: A function for implementing MR-APSS.

In YangLabHKUST/MR-APSS: The MRAPSS package implement the MR-APPSS approach to test for the causal effect of an exposure on a outcome disease.

A function for implementing MR-APSS.

Description

MR-APSS: a unified approach to Mendelian Randomization accounting for pleiotropy and sample structure using genome-wide summary statistics. MA-APSS uses a variantional EM algorithm for estimation of parameters. MR-APSS uses likelihood ratio test for inference.

Usage

MRAPSS(
  MRdat = NULL,
  exposure = "exposure",
  outcome = "outcome",
  pi0 = NULL,
  sigma.sq = NULL,
  tau.sq = NULL,
  C = matrix(c(1, 0, 0, 1), 2, 2),
  Omega = matrix(0, 2, 2),
  Cor.SelectionBias = T,
  tol = 1e-08,
  ELBO = F
)

Arguments

MRdat	data frame at least contain the following varaibles: b.exp b.out se.exp se.out L2 Threshold. L2:LD score, Threshold: modified IV selection threshold for correction of selection bias
exposure	exposure name
outcome	outcome name
pi0	initial value for pi0, default 'NULL' will use the default initialize procedure.
sigma.sq	initial value for sigma.sq , default 'NULL'will use the default initialize procedure.
tau.sq	initial value for tau.sq , default 'NULL' will use the default initialize procedure.
C	the estimated C matrix capturing the effects of sample structure. default 'diag(2)'.
Omega	the estimated variance-covariance matrix of polygenic effects. default 'matrix(0,2,2)'.
Cor.SelectionBias	Whether use the selection Threshold for correction of selection bias. If FALSE, the model won't correct for selection bias.
tol	tolerence, default '1e-08'
ELBO	Whether check the evidence lower bound or not, if 'FALSE', check the maximum likelihood instead. default 'FALSE'.

Value

a list with the following elements:

MRdat:

Input data frame

exposure:

exposure of interest

outcome:

outcome of interest

beta:

causal effect estimate

beta.se:

standard error

pval:

p-value

sigma.sq:

variance of forground exposure effect

tau.sq:

variance of forground outcome effect

pi0:

The probability of a SNP with forground signal after selection

post:

Posterior estimates of latent varaibles

method:

"MR-APSS"

Examples

library(MRAPSS)
exposure = "BMI"
outcome = "T2D"
Threshold = 5e-05  # IV selection Threshold
data(C)
data(Omega)
data(MRdat)
MRres = MRAPSS(MRdat,
               exposure = "BMI",
               outcome = "T2D",
               C = C,
               Omega =  Omega ,
               Cor.SelectionBias = T)
MRplot(MRres, exposure = "BMI", outcome = "T2D")

YangLabHKUST/MR-APSS documentation built on April 13, 2025, 7:56 p.m.