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A Bayesian nonparametric semi-supervised model for integration of multiple single-cell experiments
[article]
2020
bioRxiv
pre-print
Joint analysis of multiple single cell RNA-sequencing (scRNA-seq) data is confounded by technical batch effects across experiments, biological or environmental variability across cells, and different capture processes across sequencing platforms. Manifold alignment is a principled, effective tool for integrating multiple data sets and controlling for confounding factors. We demonstrate that the semi-supervised t-distributed Gaussian process latent variable model (sstGPLVM), which projects the
doi:10.1101/2020.01.14.906313
fatcat:htsstup2njd4xhf667snjogo4e