Last updated: 2020-05-25
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Knit directory: analysis_pipelines/
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FUSION
softwareFUSION
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 libraries.
install.packages(c('optparse','RColorBrewer'))
install.packages('plink2R-master/plink2R/',repos=NULL)
install.packages(c('glmnet','methods'))
Please see the detail instructions: http://gusevlab.org/projects/fusion/
FUSION
website (http://gusevlab.org/projects/fusion/) provides very detailed instructions and examples to run TWAS analysis, compute your own weights, and conditional analysis, etc.
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