kTWAS: integrating kernel-machine with transcriptome-wide association studies improves statistical power and reveals novel genes
The kTWAS program leverages TWAS-like feature selection (Elastic Net weights) followed by a SKAT-like kernel-based score test, to combine advantages from both approaches.
kTWAS is a batteries-included JAR executable. All needed external jar packages are included in the downloadable, kTWAS.jar. To download all necessary files, users can use the command
git clone https://github.com/theLongLab/kTWAS.git
As we used an R package SKAT, the users have to install R and SKAT (https://cran.r-project.org/web/packages/SKAT/index.html.) The versions of R and R package SKAT that we have used on our platform are: version 2.0.0 for SKAT and version 3.5.1 for R. Other versions are not tested, although they may work. Users are also expected to have java (version: 1.8) on their platform. plink (v1.07, https://zzz.bwh.harvard.edu/plink/download.shtml) should also be installed.
Usage:
java -jar kTWAS.jar kTWAS -format csv|plink -input_genotype INPUT_GENOTYPE_FILE -input_phenotype INPUT_PHENOTYPE_FILE -input_phenotype_column INPUT_PHENOTYPE_COLUMN_START:2 -input_phenotype_type PHENOTYPE_TYPE: continuous|binary -en_info_path INPUT_ELASTICNET_INFORMATION_FILE -gene INPUT_ENSEMBL_GENE_ID -plink PLINK_BINARY_FILE_PATH -Rscript RSCRIPT_BINARY_FILE_PATH -output_folder OUTPUT_FOLDER_PATH
Installation and a simple example are described below. Users can get the final p-value result under the folder: OUTPUT_FOLDER_PATH.
You may try our example after "git clone". If trying csv format, the command line is:
java -jar kTWAS.jar kTWAS -format csv -input_genotype EXAMPLE/CSV_FORMAT/example.csv -input_phenotype EXAMPLE/CSV_FORMAT/example.tsv -input_phenotype_column 2 -input_phenotype_type binary -en_info_path ElasticNet_DB/ElasticNet_Whole_Blood.txt -gene ENSG00000250334.5 -plink /PATH/TO/plink -Rscript /PATH/TO/Rscript -output_folder /PATH/TO/OUT_FOLDER
Otherwise, if users want to try plink format, the command line is:
java -jar kTWAS.jar kTWAS -format plink -input_genotype EXAMPLE/PLINK_FORMAT/example.tped -input_phenotype EXAMPLE/PLINK_FORMAT/example.tfam -input_phenotype_column 6 -input_phenotype_type binary -en_info_path ElasticNet_DB/ElasticNet_Whole_Blood.txt -gene ENSG00000250334.5 -plink /PATH/TO/plink -Rscript /PATH/TO/Rscript -output_folder /PATH/TO/OUT_FOLDER
Please note that, to consistent with plink format, the phenotype is set to missing (normally represented by -9) if unspecified. It must be a numeric value. Case/control phenotypes are normally coded as control = 1, case = 2.The kTWAS.result under /PATH/TO/OUT_FOLDER is the final output file by kTWAS. More description and benchmarking of kTWAS can be found in our publication:https://www.biorxiv.org/content/10.1101/2020.06.29.177121v1.full.pdf
If you use the elastic net database in analysis, please cite:
"The GTEx Consortium atlas of genetic regulatory effects across human tissues", Aguet et al, 2019, preprint
"A gene-based association method for mapping traits using reference transcriptome data", Gamazon et al, 2015, Nature Genetics
"Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics", Barbeira et al, 2018, Nature Communications
It it asked by the PrediXcan authors, please refer to: http://predictdb.org/
Chen Cao, [email protected]
Quan Long, [email protected]
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