Fig. 1From: Multi-omics differentially classify disease state and treatment outcome in pediatric Crohn’s diseaseDiagram of the different datasets used for classification in this study. Datasets in orange were derived from the shotgun metagenomic sequencing (MGS) data (n = 40) and the datasets in blue were derived from the 16S rRNA gene (16S) sequencing data (n = 38*). These datasets were used to classify both disease state and treatment response as input to random forest machine learning models. *Note two Crohn’s disease samples were removed from both the 16S sequencing and MGS datasets due to low sequencing coverage, but their genetic profile was inferred from the MGSBack to article page