From ba9ebe298acf4aab19c39a426465970037a2a3c6 Mon Sep 17 00:00:00 2001 From: Oleksandr Frei Date: Sun, 9 Dec 2018 22:52:00 +0100 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 2e8e88c..e36fa4d 100644 --- a/README.md +++ b/README.md @@ -311,7 +311,7 @@ Results of univariate analysis: * ``['univariate'][0]['qq_plot_bins_data'][]`` - a 3x3 matrix of QQ plots, partitioned by MAF and LD score; ```` can take values 0 to 8; each QQ plot follows the format defined above; the ranges of MAF and LD score for each bin is specified in ``['univariate'][0]['qq_plot_bins_data'][]['title']``. Results of bivariate analysis: -* ``['bivariate']['params'][]`` - point estimates of model parameters. Here ```` can be one of the following: ``pi_vec`` - polygenicty of each component (fraction of variants specific to the first trait, specific to the second trait, and shared across traits); ``rho_beta`` - correlation of effect sizes within each component (first two values are zeros); ``rho_zero`` - correlation of residuals; ``sig2_beta`` - 2x3 matrix, variance of effect sizes for each trait and within each component; ``sig2_zero`` - variance distortion in each trait. -* ``['bivariate']['ci'][][]`` - uncertainty of parameter estimates. Here ```` can be one of the following: ``h2_T1``, ``h2_T2`` - heritability of the first and the second traits; ``pi1u``, ``pi2u`` total polygenicity of the first and of the second trait; ``pi_vec_C1``, ``pi_vec_C2``, ``pi_vec_C3`` - polygenicity of the three components in the model; ``rg`` - genetic correlation; ``rho_beta`` - correlation of effect sizes within shared polygenic component; ``rho_zero`` - correlation of residuals; ``sig2_beta_T1``, ``sig2_beta_T2`` - variance of effect sizes in the first and in the second trait; ``sig2_zero_T1``, ``sig2_zero_T1`` - variance distortion in the first and in the second trait.) +* ``['bivariate']['params'][]`` - point estimates of model parameters. Here ```` can be one of the following: ``pi_vec`` - polygenicty of each component (fraction of variants specific to the first trait, specific to the second trait, and shared across traits); ``rho_beta`` - correlation of effect sizes within each component (first two values are zeros); ``rho_zero`` - covariance inflation parameter; ``sig2_beta`` - 2x3 matrix, variance of effect sizes for each trait and within each component; ``sig2_zero`` - variance distortion in each trait. +* ``['bivariate']['ci'][][]`` - uncertainty of parameter estimates. Here ```` can be one of the following: ``h2_T1``, ``h2_T2`` - heritability of the first and the second traits; ``pi1u``, ``pi2u`` total polygenicity of the first and of the second trait; ``pi_vec_C1``, ``pi_vec_C2``, ``pi_vec_C3`` - polygenicity of the three components in the model; ``rg`` - genetic correlation; ``rho_beta`` - correlation of effect sizes within shared polygenic component; ``rho_zero`` - covariance inflation parameter; ``sig2_beta_T1``, ``sig2_beta_T2`` - variance of effect sizes in the first and in the second trait; ``sig2_zero_T1``, ``sig2_zero_T1`` - variance distortion in the first and in the second trait.) * ``['bivariate']['stratified_qq_plot_fit_data'][][]`` - data for stratified QQ plots. Here ```` can be either ``'trait1'`` or ``'trait2'``; ```` can be ``0``, ``1``, ``2`` or ``3``. Stratified QQ plots are made both ways (i.e. ``trait1|trait2``, and ``trait2||trait1``; hense the ```` defines which trait is primary (so that stratified QQ plots are conditioned on the other trait. ```` equal to ``0`` means a stratum of all SNPs, ``1``, ``2`` and ``3`` are increased levels of association on the secondary trait. Each QQ plot has format defined above (see results of univariate analysis).