Ryan, Feargal Additional file 3: of Application of machine learning techniques for creating urban microbial fingerprints Figure S3. t-SNE output to represent microbial profiles on two dimensions. Spearman dissimilarities were calculated from a set of 2239 taxonomic features which represent those present in at least 5% of samples with a minimum relative abundance of 0.1% in a single sample. Confidence regions are 70% confidence regions showing surface type. (PDF 85 kb) Microbiome;Machine learning;Public health;Urban;Bioinformatics;Microbiota 2019-08-17
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