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Papers: 10.26508/lsa.202001004

https://doi.org/10.26508/lsa.202001004

CellMixS: quantifying and visualizing batch effects in single-cell RNA-seq data

Cited by: 21
Author(s): Almut Luetge, Joanna Zyprych-Walczak, Urszula Brykczynska Kunzmann, Helena L. Crowell, Daniela Calini, Dheeraj Malhotra, Charlotte Soneson, Mark D. Robinson
Published: over 4 years ago

Software Mentions 12

bioconductor: CellMixS
Evaluate Cellspecific Mixing
Papers that mentioned: 1
Very Likely Science (94)
bioconductor: ComplexHeatmap
Make Complex Heatmaps
Papers that mentioned: 565
Very Likely Science (90)
bioconductor: countsimQC
Compare Characteristic Features of Count Data Sets
Papers that mentioned: 6
Very Likely Science (100)
bioconductor: muscat
Multi-sample multi-group scRNA-seq data analysis tools
Papers that mentioned: 4
Very Likely Science (100)
bioconductor: scater
Single-Cell Analysis Toolkit for Gene Expression Data in R
Papers that mentioned: 79
Very Likely Science (100)
bioconductor: scDblFinder
scDblFinder
Papers that mentioned: 7
Very Likely Science (100)
bioconductor: scran
Methods for Single-Cell RNA-Seq Data Analysis
Papers that mentioned: 113
Very Likely Science (100)
bioconductor: SingleCellExperiment
S4 Classes for Single Cell Data
Papers that mentioned: 36
Very Likely Science (75)
cran: cms
Calculate Medicare Reimbursement
Papers that mentioned: 1
Very Likely Science (98)
cran: ggplot2
Create Elegant Data Visualisations Using the Grammar of Graphics
Papers that mentioned: 11,441
Very Likely Science (100)
cran: Seurat
Tools for Single Cell Genomics
Papers that mentioned: 1,512
Very Likely Science (100)
pypi: cms
Eraple CMS (Content Management System)
Papers that mentioned: 1
Likely Science (40)