InTACT is a command line tool for testing gene-trait associations by integrating GWAS summary statistics with gene expression levels from multiple tissues. It returns P-values for both multi- and single-tissue association analyses.
InTACT has three compelling features that make it potentially useful in identifying novel gene-trait associations:
- It is very fast and maintains higher power than benchmark methods, that is, the burden sum test (i.e., the standard TWAS) and MultiXcan.
- It effectively integrates several tissue-specific and multi-tissue gene-trait association tests via Cauchy-distribution transformation.
- Its P-value is accurate by approximating it through the standard Cauchy distribution, especially when the P-values are small.
First, clone this repository of InTACT:
git clone https://github.com/bae-y/InTACT.git
cd InTACTBefore running InTACT, you should download the following requirements into your InTACT/ directory :
plinkfrom PLINK1.9,- LD reference data (such as 1000 Genomes European ancestry data),
- the summary statistics data (such as from IGAP1) , and
- a file listing all the information for the weights files (such as TWAS/FUSION).
The file listing information for the weights files must have columns WGT, ID, CHR, GENE, P0, P1, PANEL, which will look like this:
PANEL WGT ID GENE CHR P0 P1
...
136327 Liver Liver/Liver.ENSG00000160305.13.wgt.RDat ENSG00000160305.13 DIP2A 21 47878812 47989926
143844 Lung Lung/Lung.ENSG00000228314.1.wgt.RDat ENSG00000228314.1 CYP4F29P 21 15215454 15220685
...
Also, please make sure that your R already has these libraries:
R
install.packages(c('optparse','RColorBrewer','Rcpp','RcppArmadillo','bigmemory','mvtnorm','data.table'))
devtools::install_github("gabraham/plink2R/plink2R")Once we have all the requirements, we can run InTACT with the following example command:
Rscript InTACT.R \
--sumstats IGAP1.rds \
--out out \
--weights TWAS_WEIGHTS.rds \
--weights_dir ./WEIGHTS/ \
--ref_ld_chr 1000G.EUR.MultiTissue.CHR \
--chr 21Since InTACT analyzes one chromosome at a time, chromosome number is a required input.
For each chromosome, InTACT returns two files:
- a result table of single-tissue association tests and
- a result table of multi-tissue association tests.
The first table shows single-tissue association analyses for every single tissue. The columns TWAS.P, SSU.P, ACAT.P indicate the P-values of the burden sum test (i.e., the standard TWAS), the burden score test (i.e., sum of squared U test), and the Cauchy combination test, respectively. Tk.P represents the P-value of tissue k, after combining the three tissue-specific tests.
PANEL CHR ID ... TWAS.P SSU.P ACAT.P Tk.P
...
7949 Adipose_Subcutaneous 21 ENSG00000160305.13 ... 0.4863835 0.7773842 0.8560749 0.7605017
14172 Adipose_Visceral_Omentum 21 ENSG00000160305.13 ... 0.7925701 1.0000000 0.8213858 1.0000000
...
25074 Artery_Aorta 21 ENSG00000228314.1 ... 0.8551422 0.1066685 0.11642063 0.2283266
36475 Artery_Tibial 21 ENSG00000228314.1 ... 0.6329966 0.2443968 0.25933623 0.3494701
...
The second table shows the results from gene-trait association tests for NPANEL multiple tissues. The columns T1m.P, MultiXcan.P, InTACT.P stand for the P-values of the Cauchy-based joint test, MultiXcan, and InTACT, respectively. To compare their performance with the single-tissue test, we also provide the results for the standard TWAS (BEST.TWAS.P) to which we ought to apply the stringent Bonferroni-corrected significance threshold in further analysis.
CHR ID ... NPANEL ... BEST.TWAS.P T1m.P MultiXcan.P InTACT.P ...
...
87 21 ENSG00000160305.13 ... 28 ... 0.1266740 1.0000000 0.4540494 1.0000000 ...
120 21 ENSG00000228314.1 ... 22 ... 0.1512981 0.5228292 0.1193236 0.2166768 ...
...
If you use the software, please cite
Bae, Y. E., Wu, L. & Wu, C. InTACT: An adaptive and powerful framework for joint-tissue transcriptome-wide association studies. Genetic Epidemiology gepi.22425 (2021).
Ye Eun Bae (Department of Statistics, Florida State University)