A track of Nature Methods papers related to transcriptome analysis and machine learning.
(Up to Feb 4, 2020)
- Probabilistic cell typing enables fine mapping of closely related cell types in situ
- Fast, sensitive and accurate integration of single-cell data with Harmony
- Supervised classification enables rapid annotation of cell atlases
- Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling
- scGen predicts single-cell perturbation responses
- Joint analysis of heterogeneous single-cell RNA-seq dataset collections