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Papers: 10.1186/s13059-021-02480-2

https://doi.org/10.1186/s13059-021-02480-2

Evaluation of some aspects in supervised cell type identification for single-cell RNA-seq: classifier, feature selection, and reference construction

Cited by: 16
Author(s): Wenjing Ma, Kenong Su, Hao Wu
Published: almost 4 years ago

Software Mentions 12

bioconductor: CHETAH
Fast and accurate scRNA-seq cell type identification
Papers that mentioned: 6
Very Likely Science (100)
bioconductor: FEAST
FEAture SelcTion (FEAST) for Single-cell clustering
Papers that mentioned: 87
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: irlba
Fast Truncated Singular Value Decomposition and Principal Components Analysis for Large Dense and Sparse Matrices
Papers that mentioned: 16
Very Likely Science (100)
cran: SAVER
Single-Cell RNA-Seq Gene Expression Recovery
Papers that mentioned: 40
Very Likely Science (100)
cran: scSorter
Implementation of 'scSorter' Algorithm
Papers that mentioned: 2
Very Likely Science (93)
cran: Seurat
Tools for Single Cell Genomics
Papers that mentioned: 1,512
Very Likely Science (100)
pypi: Harmony
Harmony Programming Language
Papers that mentioned: 504
Very Likely Science (65)
pypi: ItClust
An Iterative Transfer learning algorithm for scRNA-seq Clustering
Papers that mentioned: 2
Very Likely Science (100)
pypi: scikit-learn
A set of python modules for machine learning and data mining
Papers that mentioned: 2,431
Very Likely Science (100)
pypi: scmap
Assigns rgb colors to points on sphere.
Papers that mentioned: 34
Very Likely Science (65)
pypi: sklearn
deprecated sklearn package, use scikit-learn instead
Papers that mentioned: 559
Very Likely Science (65)