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Bayesian Unidimensional Scaling for visualizing uncertainty in high dimensional datasets with latent ordering of observations

Detecting patterns in high-dimensional multivariate datasets is non-trivial. Clustering and dimensionality reduction techniques often help in discerning inherent structures. In biological datasets such as microbial community composition or gene expression data, observations can be generated from a continuous process, often unknown. |