Last updated: 2020-06-03
Checks: 6 1
Knit directory: QGT-Columbia-HKI/
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export DATA=$PRE/s-predixcan/data
export MODEL=$PRE/models
export METAXCAN=$PRE/MetaXcan-master/software
export OUTPUT=$PRE/results
<!-- export METAXCAN=/Users/haekyungim/Desktop/local-analysis/QGT-Columbia-HKI/MetaXcan-master/software -->
<!-- export DATA=/Users/haekyungim/Desktop/local-analysis/QGT-Columbia-HKI/predixcan/data -->
<!-- export RESULTS=/Users/haekyungim/Desktop/local-analysis/QGT-Columbia-HKI/predixcan/results -->
<!-- mkdir $RESULTS -->
printf "Predict expression\n\n"
python3 $METAXCAN/Predict.py \
--model_db_path $DATA/models/gtex_v8_en/en_Whole_Blood.db \
--vcf_genotypes $DATA/1000G_hg38/ALL.chr22.shapeit2_integrated_snvindels_v2a_27022019.GRCh38.phased.vcf.gz \
--vcf_mode genotyped \
--variant_mapping $DATA/gtex_v8_eur_filtered_maf0.01_monoallelic_variants.txt.gz id rsid \
--on_the_fly_mapping METADATA "chr{}_{}_{}_{}_b38" \
--prediction_output $RESULTS/vcf_1000G_hg38_en/Whole_Blood__predict.txt \
--prediction_summary_output $RESULTS/vcf_1000G_hg38_en/Whole_Blood__summary.txt \
--verbosity 9 \
--throw
printf "association\n\n"
python3 $METAXCAN/PrediXcanAssociation.py \
--expression_file $RESULTS/vcf_1000G_hg38_en/Whole_Blood__predict.txt \
--input_phenos_file $DATA/1000G_hg38/random_pheno_1000G_hg38.txt \
--input_phenos_column pheno \
--output $RESULTS/vcf_1000G_hg38_en/Whole_Blood__association.txt \
--verbosity 9 \
--throw
export PRE=/Users/haekyungim/Box/LargeFiles/QGT-Columbia-HKI
export DATA=$PRE/s-predixcan/data
export MODEL=$PRE/models
export METAXCAN=$PRE/MetaXcan-master/software
export OUTPUT=$PRE/results
echo $PRE
echo $DATA
echo $MODEL
echo $METAXCAN
echo $OUTPUT
/Users/haekyungim/Box/LargeFiles/QGT-Columbia-HKI
/Users/haekyungim/Box/LargeFiles/QGT-Columbia-HKI/s-predixcan/data
/Users/haekyungim/Box/LargeFiles/QGT-Columbia-HKI/models
/Users/haekyungim/Box/LargeFiles/QGT-Columbia-HKI/MetaXcan-master/software
/Users/haekyungim/Box/LargeFiles/QGT-Columbia-HKI/results
echo $PRE
export PRE=/Users/haekyungim/Box/LargeFiles/QGT-Columbia-HKI
export DATA=$PRE/s-predixcan/data
export MODEL=$PRE/models
export METAXCAN=$PRE/MetaXcan-master/software
export OUTPUT=$PRE/results
python $METAXCAN/SPrediXcan.py \
--gwas_file $DATA/imputed_CARDIoGRAM_C4D_CAD_ADDITIVE.txt.gz \
--snp_column panel_variant_id --effect_allele_column effect_allele --non_effect_allele_column non_effect_allele --zscore_column zscore \
--model_db_path $MODEL/gtex_v8_mashr/mashr_Whole_Blood.db \
--covariance $MODEL/gtex_v8_mashr/mashr_Whole_Blood.txt.gz \
--keep_non_rsid --additional_output --model_db_snp_key varID \
--throw \
--output_file $OUTPUT/spredixcan/eqtl/CARDIoGRAM_C4D_CAD_ADDITIVE__PM__Whole_Blood.csv
python $METAXCAN/SMulTiXcan.py \
--models_folder $DATA/models/eqtl/mashr \
--models_name_pattern "mashr_(.*).db" \
--snp_covariance $DATA/models/gtex_v8_expression_mashr_snp_covariance.txt.gz \
--metaxcan_folder $OUTPUT/spredixcan/eqtl/ \
--metaxcan_filter "CARDIoGRAM_C4D_CAD_ADDITIVE__PM__(.*).csv" \
--metaxcan_file_name_parse_pattern "(.*)__PM__(.*).csv" \
--gwas_file $OUTPUT/processed_summary_imputation/imputed_CARDIoGRAM_C4D_CAD_ADDITIVE.txt.gz \
--snp_column panel_variant_id --effect_allele_column effect_allele --non_effect_allele_column non_effect_allele --zscore_column zscore --keep_non_rsid --model_db_snp_key varID \
--cutoff_condition_number 30 \
--verbosity 7 \
--throw \
--output $OUTPUT/smultixcan/eqtl/CARDIoGRAM_C4D_CAD_ADDITIVE_smultixcan.txt
sessionInfo()R version 3.6.3 (2020-02-29)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Catalina 10.15.2
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] workflowr_1.6.2 Rcpp_1.0.4.6 rprojroot_1.3-2 digest_0.6.25
[5] later_1.0.0 R6_2.4.1 backports_1.1.6 git2r_0.26.1
[9] magrittr_1.5 evaluate_0.14 stringi_1.4.6 rlang_0.4.5
[13] fs_1.4.1 promises_1.1.0 rmarkdown_2.1 tools_3.6.3
[17] stringr_1.4.0 glue_1.4.1 httpuv_1.5.2 xfun_0.13
[21] yaml_2.2.1 compiler_3.6.3 htmltools_0.4.0 knitr_1.28