Version bump
Zero-inflated Negative Binomial based Wanted Variation Extraction (ZINB-WaVE)
This package implements a zero-inflated negative binomial model for single-cell RNA-seq data, with latent factors.
The model is described in details in the paper:
D. Risso, F. Perraudeau, S. Gribkova, S. Dudoit and JP. Vert (2018). A general and flexible method for signal extraction from single-cell RNA-seq data. Nature Communications.
Since Bioconductor 3.7 the new recommended way to install Bioconductor packages is via the BiocManager package, available on CRAN:
install.packages("BiocManager") BiocManager::install("zinbwave")
Note that zinbwave requires R (>=3.4) and Bioconductor (>=3.6).
zinbwave
R (>=3.4)
Bioconductor (>=3.6)
In virtually all cases, installing from Bioconductor is recommended. However, if you want to install the development version of zinbwave from GitHub, you can do so with the following.
library(devtools) install_github("drisso/zinbwave")
用于单细胞RNA测序数据的零膨胀负二项模型分析
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zinbwave
Zero-inflated Negative Binomial based Wanted Variation Extraction (ZINB-WaVE)
This package implements a zero-inflated negative binomial model for single-cell RNA-seq data, with latent factors.
The model is described in details in the paper:
D. Risso, F. Perraudeau, S. Gribkova, S. Dudoit and JP. Vert (2018). A general and flexible method for signal extraction from single-cell RNA-seq data. Nature Communications.
Installation
Since Bioconductor 3.7 the new recommended way to install Bioconductor packages is via the BiocManager package, available on CRAN:
Note that
zinbwaverequiresR (>=3.4)andBioconductor (>=3.6).In virtually all cases, installing from Bioconductor is recommended. However, if you want to install the development version of
zinbwavefrom GitHub, you can do so with the following.