We created random forests (RF) models trained on subsets of IFN- and IFN+ TB patients and non-TB controls and tested performances of five different sizes of gene signatures derived from these models to determine whether IFN- and IFN+ TB patient groups’ signatures differed. This evidence concerns the gene IFNA1 and tuberculosis.