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Simulation and analysis scripts for paper "Reconsidering the validity of transcriptome-wide association studies"

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cadeleeuw/twas-validity-scripts2022

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This repository contains the simulation and analysis scripts for the paper "Reconsidering the validity of transcriptome-wide association studies" (preprint). Content by directory is as follows:

main: scripts for real data analysis

  • run_bivar.r: runs LAVA-rG and LAVA-TWAS
  • run_fusion.bs: runs FUSION

lava: scripts for parts of LAVA analysis external to LAVA R package

  • lava_twas.r: LAVA-TWAS code
  • lava_approx.r: normal approximation for LAVA-rG bivariate analysis

simulations: scripts for generation and analysis of simulated data

  • generate.r: generates input for all the analysis (both raw E and Y, and corresponding SNP summary statistics)
    • there are 10 different data blocks (from chromosomes 1-10), results are aggregated over thes blocks
    • each call generates 100 iterations for the specified phenotype sample size and number of SNPs
    • simulated values are generated for the full range of (relevant) heritability and expression sample size values
  • run_comm.r: run CoMM analysis for a specific pair of conditions at a time
    • uses raw E and Y
  • run_lava.r: run LAVA-TWAS analysis for all pairs of the list of input conditions (for specific number of SNPs in the block)
    • all analyses use the N=1000 genotype block as reference data, regardless of the sample sizes used when generating the data
    • uses summary statistics for both E and Y
  • fusion_weights.bs: fits prediction models (BLUP, BSLMM, Elastic Net, LASSO) on the simulated expression
    • to make simulations computationally more feasible, cross-validation is turned off, and true r2 values used in the simulation process are provided to FUSION
    • uses raw E
  • fusion_analysis.bs: runs TWAS analysis with fitted prediction models, for all combinations of expression and outcome conditions for given outcome sample size
    • all analyses use the N=1000 genotype block as reference data, regardless of the sample sizes used when generating the data
    • uses summary statistics for Y
  • fusion (directory): contains three R helper scripts used in fusion_weights.bs and fusion_analysis.bs

figure data.zip additional archive with scripts and input data to generate the main text figures

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Simulation and analysis scripts for paper "Reconsidering the validity of transcriptome-wide association studies"

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