PrediXcan v7 model for Korean terminal ileum tissues

The genotypes and gene expression datasets were collected from Korean population.

• Genotype data: Park, S.K.; Kim, Y.B.; Kim, S.; Lee, C.W.; Choi, C.H.; Kang, S.B.; Kim, T.O.; Bang, K.B.; Chun, J.; Cha, J.M., et al. Development of a Machine Learning Model to Predict Non-Durable Response to Anti-TNF Therapy in Crohn's Disease Using Transcriptome Imputed from Genotypes. J Pers Med 2022, 12.
• RNA-seq data: Park, S.K.; Kim, S.; Lee, G.Y.; Kim, S.Y.; Kim, W.; Lee, C.W.; Park, J.L.; Choi, C.H.; Kang, S.B.; Kim, T.O., et al. Development of a Machine Learning Model to Distinguish between Ulcerative Colitis and Crohn's Disease Using RNA Sequencing Data. Diagnostics (Basel) 2021, 11.

The Korean PrediXcan v7 models were developed according to the original PrediXcan GTEx v7 tutorial.

The sample size for the training was 61, while that of the validation was 46. The two sets were from different individuals and different batches based on different library preparation protocols.