README.md

In abuchardt/EdGwas: Joint regression Analysis of Multiple traits based on GENEtic relationships

geneJAM

The goal of geneJAM is to help clustering outcome components (traits) that share some feature (genetic component) using polygenic risk scores (PRS).

Installation

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("abuchardt/geneJAM")

Example

This is a basic example on simulated data:

library(geneJAM)
N <- 1000 #
q <- 10 #
p <- 5000 #
set.seed(1)
# Sample 1
X0 <- matrix(rbinom(n = N*p, size = 2, prob = 0.3), nrow=N, ncol=p)
B <- matrix(0, nrow = p, ncol = q)
B[1, 1:2] <- 1
B[3, 3] <- 2
Y0 <- X0 %*% B + matrix(rnorm(N*q), nrow = N, ncol = q)

Compute polygenic scores and coefficients

psobj <- ps.geneJAM(X0, Y0)
ps <- psobj$PS
beta <- psobj$beta

Create new sample

X <- matrix(rbinom(n = N*p, size = 2, prob = 0.3), nrow=N, ncol=p)
Y <- X %*% B + matrix(rnorm(N*q), nrow = N, ncol = q)
PS <- X %*% beta

Run geneJAM

fit <- geneJAM(PS, Y)

Plot mean standard error curve

plot(fit, 1)

Plot estimated optimal adjacency matrix

plot(fit, 2)

abuchardt/EdGwas documentation built on Nov. 28, 2022, 11:49 a.m.