M3Drop
Michaelis-Menten Modelling of Dropouts in single-cell RNASeq
Bioconductor version: 3.23 · Package version: 1.38.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
This package fits a model to the pattern of dropouts in single-cell RNASeq data. This model is used as a null to identify significantly variable (i.e. differentially expressed) genes for use in downstream analysis, such as clustering cells. Also includes an method for calculating exact Pearson residuals in UMI-tagged data using a library-size aware negative binomial model.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("M3Drop")Details
| Maintainer | Tallulah Andrews <tallulandrews@gmail.com> |
| Author | Tallulah Andrews <tallulandrews@gmail.com> |
| License | GPL (>=2) |
| URL | https://github.com/tallulandrews/M3Drop |
| Bug Reports | https://github.com/tallulandrews/M3Drop/issues |
| Source branch | RELEASE_3_23 |
| Build report | Bioconductor build system, r-universe |
| biocViews | DifferentialExpression, DimensionReduction, FeatureExtraction, GeneExpression, RNASeq, Sequencing, Software, Transcriptomics |
| Package Short Url | https://bioconductor.org/packages/M3Drop/ |
Citation
From within R, enter citation("M3Drop"):
Tallulah Andrews. M3Drop: Michaelis-Menten Modelling of Dropouts in single-cell RNASeq. doi:10.18129/B9.bioc.M3Drop, R package version 1.38.0, https://bioconductor.org/packages/M3Drop.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | M3Drop_1.38.0.tar.gz |
| Windows binary (x86_64) | M3Drop_1.38.0.zip |
| macOS binary (arm64) | M3Drop_1.38.0.tgz |
| macOS binary (x86_64) | M3Drop_1.38.0.tgz |
Dependencies
Depends: R (>= 3.4), numDeriv
Imports: RColorBrewer, gplots, bbmle, statmod, grDevices, graphics, stats, matrixStats, Matrix, irlba, reldist, Hmisc, methods, scater
Suggests: ROCR, knitr, M3DExampleData, SingleCellExperiment, Seurat, Biobase
Reverse dependencies
Imports Me (1): scMerge