Posts

Introduction The reference genotype database has been widely used for GWA studieds. It provides more information on the genetic variants when the individual-level genotype data is not available or the genotypes data has low sequencing depth.

Working with the summary association statistics has been important in current GWAS studies. However, generated from different cohorts, the format of summary association statistics varies a lot. In this post, we discuss how to do the preprocessing for summary association statistics.

To do simulation with genetic data, we need to make some preparion. First, we detemine the snplist and individuals in the genotype data: snplist.txt Prepare data for package bigsnpr and bigstatsr

First, we generate the ld score based on the genotype file. This function only need be estimated once module load ldsc source activate ldsc-1.0.1 ldsc.py –bfile geno –ld-wind-cm 1 –out chr1_select ldsc.

My dissertation research always needs to do comparison with the GCTA-GREML method. GCTA is a wonderful software designed for the dealing with the GWAS data. On the other hand, it does not always fit in the common statistical simulation pipeline, particualy for the software R.