Forest Fire Clustering for Single-cell Sequencing with Iterative Label Propagation and Parallelized Monte Carlo Simulation. (arXiv:2103.11802v4 [cs.LG] UPDATED)

In the era of single-cell sequencing, there is a growing need to extract
insights from data with clustering methods. Here, we introduce Forest Fire
Clustering, an efficient and interpretable method for cell-type discovery from
single-cell data. Forest Fire Clustering makes minimal prior assumptions and,
different from current approaches, calculates a non-parametric posterior
probability that each cell is assigned a cell-type label. These posterior
distributions allow for the evaluation of a label confidence for each cell and
enable the computation of …

arxiv clustering iterative sequencing simulation