In JianqiaoWang/MaxBlock:

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

MaxBlock

The goal of MaxBlock is to detect the simultatenous signal between two outcomes.

Installation

You can install the released version of MaxBlock from github with:

devtools::install_github("JianqiaoWang/MaxBlock")

Example

This is a basic example which shows you how to solve a common problem. The input is

data for outcome 1 $(X_1, Y_1)$
data for outcome 2 $X_2, Y_2$
A list of block range: each element of the list contains the index of variants within the block.

library(MaxBlock)
## basic example code
# ------------------------------- calculate the blockwise statistics
X.1 = data.list$X
Y.1 = data.list$Y1
Y.2 = data.list$Y2
Block.list = data.list$index
z.block <- matrix(NA, nrow = 1000, ncol = 2)
for(i in 1:1000){
   z.block[i,]  =  Z.Block(X.1 = X.1[, Block.list[[i]] ], X.2 = X.1[, Block.list[[i]] ],
           outcome.1 = Y.1, outcome.2 =Y.2, )
}
# ------------------------------- Max test 
maxtest(T1 = (z.block[,1])^2, T2 = (z.block[,2])^2)
# ------------------------------- Stepwise block selection 
StepSelect(z.block, alpha = 0.05 )

Plink for haplotype block estimation

One may also need to install PLINK for haplotype block estimation, and prepare a suitable reference dataset for PLINK. One resource of the reference dataset of the European population, which is also used in our paper, is the 1000 genome European reference panel downloaded here http://fileserve.mrcieu.ac.uk/ld/data_maf0.01_rs_ref.tgz, from the MRCIEU cite.

With the reference file data_maf0.01_rs.bed, data_maf0.01_rs.bim, data_maf0.01_rs.fam, we estimate the haplotype blocks for each chromosome. Files Chr_1_SNP.csv ... Chr_22_SNP.csv contain the genetic variants ID for chromosome 1-22 in our study. The output files contains the snp ID within each block. More details can be found in https://zzz.bwh.harvard.edu/plink/ld.shtml#blox.

chr = 1`
command = paste("plink --bfile data_maf0.01_rs --extract Chr_",chr,"_SNP.csv --blocks no-pheno-req no-small-max-span --blocks-strong-lowci 0.5005 --out chr_",chr, sep = "")