Last updated: 2020-05-26

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Install the FUSION software

FUSION software is implemented in R. Installation is easy: simply download and unpack the FUSION software package from github: https://github.com/gusevlab/fusion_twas

wget https://github.com/gusevlab/fusion_twas/archive/master.zip
unzip master.zip
cd fusion_twas-master

Then, install required R libraries.

install.packages(c('optparse','RColorBrewer'))
install.packages('plink2R-master/plink2R/',repos=NULL)
install.packages(c('glmnet','methods'))

You might need to install other libraries or packages to compute your own weights.

Please see the detail instructions: http://gusevlab.org/projects/fusion/

Run TWAS analysis

FUSION website (http://gusevlab.org/projects/fusion/) provides detail instructions and examples to run TWAS analysis, compute your own weights, and joint/conditional analysis, etc.

The website includes pretrained weights for RNA-seq data from GTEx and TCGA. It is straightforward to run TWAS using their pretrained weights.

Compute your own weights

If you want to compute your own weights, please follow their instructions in the section “Computing your own functional weights”. You will need to compute weights one gene at a time.

  1. Prepare the input genotype and expression (or other molecular trait) data for each gene
  2. Run FUSION.compute_weights.R function for each gene, one gene at a time
  3. After all genes have been evaluated, make a WGTLIST file which lists paths to each of the *.RDat files that were generated and call Rscript utils/FUSION.profile_wgt.R <WGTLIST> to output a per-gene profile as well as an overall summary of the data and model performance.

Reference

  • Gusev et al. “Integrative approaches for large-scale transcriptome-wide association studies” 2016 Nature Genetics

sessionInfo()
R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)

Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] workflowr_1.6.0

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.3        rprojroot_1.3-2   digest_0.6.23     later_1.0.0      
 [5] R6_2.4.1          backports_1.1.5   git2r_0.26.1.9000 magrittr_1.5     
 [9] evaluate_0.14     stringi_1.4.5     rlang_0.4.4       fs_1.3.1         
[13] promises_1.1.0    whisker_0.4       rmarkdown_2.1     tools_3.5.1      
[17] stringr_1.4.0     glue_1.3.1        httpuv_1.5.2      xfun_0.12        
[21] yaml_2.2.0        compiler_3.5.1    htmltools_0.4.0   knitr_1.28