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Papers: 10.15252/msb.20209620

https://doi.org/10.15252/msb.20209620

Probabilistic harmonization and annotation of single‐cell transcriptomics data with deep generative models

Cited by: 166
Author(s): Chenling Xu, Romain Lopez, Edouard Mehlman, Jeffrey Regier, Michael I. Jordan, Nir Yosef
Published: over 4 years ago

Software Mentions 9

bioconductor: edgeR
Empirical Analysis of Digital Gene Expression Data in R
Papers that mentioned: 6,568
Very Likely Science (100)
bioconductor: limma
Linear Models for Microarray Data
Papers that mentioned: 7,776
Very Likely Science (78)
bioconductor: M3Drop
Michaelis-Menten Modelling of Dropouts in single-cell RNASeq
Papers that mentioned: 21
Very Likely Science (100)
bioconductor: scmap
A tool for unsupervised projection of single cell RNA-seq data
Papers that mentioned: 34
Very Likely Science (100)
cran: Seurat
Tools for Single Cell Genomics
Papers that mentioned: 1,512
Very Likely Science (100)
pypi: MNN
C methods for MNN Package
Papers that mentioned: 12
Very Likely Science (80)
pypi: PhenoGraph
Graph-based clustering for high-dimensional single-cell data
Papers that mentioned: 96
Very Likely Science (100)
pypi: scmap
Assigns rgb colors to points on sphere.
Papers that mentioned: 34
Very Likely Science (65)
pypi: SymSim
Tool for simulating planes of symmetries assuming kinematic diffraction
Papers that mentioned: 7
Very Likely Science (100)