Last updated: 2021-01-26

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Knit directory: mmbr-rss-dsc/

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This is result from our mvSuSiE RSS simulation using UKB data. There are 600 datasets. The max PVE across traits is 0.0005.

For each dataset, we simulate signals using 2 type of priors, the details are here

  1. Artificial mixture: 20 conditions. The oracle residual variance is a diagonal matrix.

  2. UKB Bloodcells mixture: 16 conditions. The oracle residual variance is a dense matrix.

We estimate prior weights using ‘EM’ method.

Overall: Ignoring correlation between conditions in residual matrix results in poor fit. Joint modeling improves power.

Global comparison

We compare the CS and PIP for each SNP.

PIP calibration

Artificial Mixture

UKB Bloodcells Mixture

Power

Artificial Mixture

  1. Comparing different residuals
  1. Comparing different priors

UKB Bloodcells Mixture

  1. Comparing different residuals
  1. Comparing different priors

CS

Artificial Mixture

mnm_rss_naive and mnm_rss_ed+oracle have overlapping CSs.

  1. Comparing different residuals
  1. Comparing different priors

UKB Bloodcells Mixture

  1. Comparing different residuals
  1. Comparing different priors

Trait specific comparison

We compare the CS and PIP for each SNP in each trait.

PIP calibration

Artificial Mixture

UKB Bloodcells Mixture

Power

Artificial Mixture

  1. Comparing different residuals
  1. Comparing different priors

UKB Bloodcells Mixture

  1. Comparing different residuals
  1. Comparing different priors

CS

Artificial Mixture

  1. Comparing different residuals
  1. Comparing different priors

UKB Bloodcells Mixture

  1. Comparing different residuals
  1. Comparing different priors