Last updated: 2018-05-30

Code version: 229e181

The summary statistics are from Mixed model association for biobank-scale data sets.

The \(\beta\) are coefficients from mix effects model. Since fitting the mix model with a large sample size is intractable, the author estimate them using \(\chi^2_{BOLT\_LMM\_inf}\) statistics. There is no information about how to compute se. The p value is based on \(\chi^2_{BOLT\_LMM}\) statistics. Detail about the BOLT LMM is in BOLT_LMM

The tri-allelic SNPs are excluded.

The procedure to select strong SNPs subset:

1. Select SNPs with p value less than \(5 \times 10^{-8}\).
2. For each chromosome, pick SNPs that at least 15000 bp away.

The procedure to select random SNPs subset:

1. Random select 800000 SNPs
2. For each chromosome, pick SNPs that at least 15000 bp away.

The total data set contains 11988455 SNPs. The strong subset contains 60070 SNPs. The random subset contains 142075 SNPs.

• Flash on Strong SNPs

sessionInfo()

R version 3.4.4 (2018-03-15)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.4

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] compiler_3.4.4  backports_1.1.2 magrittr_1.5    rprojroot_1.3-2
 [5] tools_3.4.4     htmltools_0.3.6 yaml_2.1.19     Rcpp_0.12.16   
 [9] stringi_1.2.2   rmarkdown_1.9   knitr_1.20      git2r_0.21.0   
[13] stringr_1.3.0   digest_0.6.15   evaluate_0.10.1

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