Development of a machine learning model to predict non- durable response to anti-TNF therapy in Crohn's disease using transcriptome imputed from genotypes

This is the expression value predicted using PrediXcan version 7 to find a gene feature that can distinguish between patients with and without effect on infliximab.

Among the various tissue models provided by PrediXcan v7, three models were selected and used: whole blood, Colon transverse, and terminal ileum of small intestine, and the predicted gene counts of each model were 6,294, 5,612 and 3,107.

For each of the three models, predicted gene expression values and phenotype information per sample were submitted.