spqn
Spatial quantile normalization
Bioconductor version: 3.24 · Package version: 1.25.0
The spqn package implements spatial quantile normalization (SpQN). This method was developed to remove a mean-correlation relationship in correlation matrices built from gene expression data. It can serve as pre-processing step prior to a co-expression analysis.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("spqn")Details
| Maintainer | Yi Wang <yiwangthu5@gmail.com> |
| Author | Yi Wang [cre, aut], Kasper Daniel Hansen [aut] |
| License | Artistic-2.0 |
| URL | https://github.com/hansenlab/spqn |
| Bug Reports | https://github.com/hansenlab/spqn/issues |
| Downloads rank | 442 |
| Source branch | devel |
| biocViews | GraphAndNetwork, NetworkInference, Normalization, Software |
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | spqn_1.25.0.tar.gz |
| Windows binary (x86_64) | spqn_1.25.0.zip |
| macOS binary (arm64) | spqn_1.25.0.tgz |
| macOS binary (x86_64) | spqn_1.25.0.tgz |
Dependencies
Depends: R (>= 4.0), ggplot2, ggridges, SummarizedExperiment, BiocGenerics
Imports: graphics, stats, utils, matrixStats
Suggests: BiocStyle, knitr, rmarkdown, tools, spqnData (>= 0.99.3), RUnit