An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.1186/s13059-020-02132-x

https://doi.org/10.1186/s13059-020-02132-x

A systematic evaluation of single-cell RNA-sequencing imputation methods

Cited by: 156
Author(s): Wenpin Hou, Zhicheng Ji, Hongkai Ji, Stephanie Hicks
Published: almost 5 years ago

Software Mentions 15

bioconductor: bayNorm
Single-cell RNA sequencing data normalization
Papers that mentioned: 3
Very Likely Science (100)
bioconductor: CellBench
Construct Benchmarks for Single Cell Analysis Methods
Papers that mentioned: 7
Very Likely Science (100)
bioconductor: limma
Linear Models for Microarray Data
Papers that mentioned: 7,776
Very Likely Science (78)
bioconductor: MAST
Model-based Analysis of Single Cell Transcriptomics
Papers that mentioned: 668
Very Likely Science (100)
bioconductor: scran
Methods for Single-Cell RNA-Seq Data Analysis
Papers that mentioned: 113
Very Likely Science (100)
bioconductor: scRecover
scRecover for imputation of single-cell RNA-seq data
Papers that mentioned: 1
Very Likely Science (100)
bioconductor: TSCAN
Tools for Single-Cell Analysis
Papers that mentioned: 49
Very Likely Science (100)
cran: DCA
Dynamic Correlation Analysis for High Dimensional Data
Papers that mentioned: 128
Very Likely Science (93)
cran: DrImpute
Imputing Dropout Events in Single-Cell RNA-Sequencing Data
Papers that mentioned: 19
Very Likely Science (100)
cran: mclust
Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
Papers that mentioned: 297
Very Likely Science (85)
cran: SAVER
Single-Cell RNA-Seq Gene Expression Recovery
Papers that mentioned: 40
Very Likely Science (100)
pypi: DCA
Count autoencoder for scRNA-seq denoising
Papers that mentioned: 128
Very Likely Science (100)
pypi: MAST
MAterials Simulation Toolkit
Papers that mentioned: 668
Very Likely Science (75)
pypi: scScope
scScope is a deep-learning based approach for single cell RNA-seq analysis.
Papers that mentioned: 7
Very Likely Science (100)
pypi: seq
Generic sequence manipulation functions
Papers that mentioned: 58
Very Likely Science (65)