Papers: 10.1371/journal.pcbi.1006245
https://doi.org/10.1371/journal.pcbi.1006245
Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database
Cited by: 213
Author(s): Luke Zappia, Belinda Phipson, Alicia Oshlack
Published: about 7 years ago
Software Mentions 17
bioconductor: DESeq2
Differential gene expression analysis based on the negative binomial distributionPapers that mentioned: 9,583
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bioconductor: edgeR
Empirical Analysis of Digital Gene Expression Data in RPapers that mentioned: 6,568
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bioconductor: scater
Single-Cell Analysis Toolkit for Gene Expression Data in RPapers that mentioned: 79
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bioconductor: scDD
Mixture modeling of single-cell RNA-seq data to identify genes with differential distributionsPapers that mentioned: 16
Very Likely Science (100)
bioconductor: scPipe
Pipeline for single cell multi-omic data pre-processingPapers that mentioned: 7
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cran: ggplot2
Create Elegant Data Visualisations Using the Grammar of GraphicsPapers that mentioned: 11,441
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pypi: plotly
An open-source, interactive data visualization library for PythonPapers that mentioned: 163
Very Likely Science (90)
pypi: umis
Package for estimating UMI counts in Transcript Tag Counting data.Papers that mentioned: 5
Very Likely Science (100)