Computer ScienceBiology

Manifold learning-based methods for analyzing single-cell RNA-sequencing data

Kevin R. Moon, Jay S. Stanley, Daniel B. Burkhardt, D. V. Dijk, Guy Wolf, Smita Krishnaswamy

2018.2.1Current Opinion in Systems Biology

DOI: 10.1016/j.coisb.2017.12.008

tlooto Summary

This review covers manifold learning-based methods for denoising the data, revealing gene interactions, extracting pseudotime progressions with model fitting, visualizing the cellular state space via dimensionality reduction, and clustering the data.

Abstract

Abstract is not available.

Citation format

MOON, Kevin R., et al. Manifold learning-based methods for analyzing single-cell RNA-sequencing data. Current Opinion in Systems Biology, 2018, 7: 36–46.