Step 0: create a sparse GRM

SAIGE and SAIGE-GENE can take sparse GRM for fitting the null model and in association tests

• This sparse GRM only needs to be created once for each data set, e.g. a biobank, and can be used for all different phenotypes as long as all tested samples are in the sparse GRM.
• Multiple programs can be used to generate a sparse GRM

1. SAIGE provides a script to create a sparse GRM *The program will output a file ended with sampleIDs.txt that contains sample IDs for the sparse GRM and a file ended with .sparseGRM.mtx that contains the sparse GRM
   • These two files can be then directly used in the next steps

    #For help information
    Rscript createSparseGRM.R --help
   

    Rscript createSparseGRM.R       \
        --plinkFile=./input/nfam_100_nindep_0_step1_includeMoreRareVariants_poly \
        --nThreads=4  \
        --outputPrefix=./output/sparseGRM       \
        --numRandomMarkerforSparseKin=2000      \
        --relatednessCutoff=0.125
   

2. GCTA

    gcta64 \
        --bfile ./input/nfam_100_nindep_0_step1_includeMoreRareVariants_poly \
        --out ./output/sparseGRM \
        --make-grm-part 3 1 \
        --maf 0.01 \
        --geno 0.15 \
        --thread-num 2
   

3. KING

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