MPAC
This is the released version of MPAC; for the devel version, see MPAC.
Multi-omic Pathway Analysis of Cells
Bioconductor version: Release (3.23)
Multi-omic Pathway Analysis of Cells (MPAC), integrates multi-omic data for understanding cellular mechanisms. It predicts novel patient groups with distinct pathway profiles as well as identifying key pathway proteins with potential clinical associations. From CNA and RNA-seq data, it determines genes’ DNA and RNA states (i.e., repressed, normal, or activated), which serve as the input for PARADIGM to calculate Inferred Pathway Levels (IPLs). It also permutes DNA and RNA states to create a background distribution to filter IPLs as a way to remove events observed by chance. It provides multiple methods for downstream analysis and visualization.
Author: Peng Liu [aut, cre] 
, Paul Ahlquist [aut], Irene Ong [aut], Anthony Gitter [aut]
Maintainer: Peng Liu <pliu55.wisc+bioconductor at gmail.com>
citation("MPAC")):Peng Liu, Paul Ahlquist, Irene Ong, Anthony Gitter. MPAC: Multi-omic Pathway Analysis of Cells. doi:10.18129/B9.bioc.MPAC, R package version 1.6.0, https://bioconductor.org/packages/MPAC.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("MPAC")For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("MPAC")| MPAC: Multi-omic Pathway Analysis of Cells | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Clustering, ImmunoOncology, RNASeq, Sequencing, Software, Survival, Technology |
| Version | 1.6.0 |
| In Bioconductor since | BioC 3.20 (R-4.4) (2 years) |
| License | GPL-3 |
| Depends | R (>= 4.4.0) |
| Imports | data.table (>= 1.14.2), SummarizedExperiment (>= 1.30.2), BiocParallel (>= 1.28.3), fitdistrplus (>= 1.1), igraph (>= 1.4.3), BiocSingular (>= 1.10.0), S4Vectors (>= 0.32.3), SingleCellExperiment (>= 1.16.0), bluster (>= 1.4.0), fgsea (>= 1.20.0), scran (>= 1.22.1), ComplexHeatmap (>= 2.16.0), circlize (>= 0.4.16), scales (>= 1.3.0), stringr (>= 1.5.1), viridis (>= 0.6.5), ggplot2 (>= 3.5.1), ggraph (>= 2.2.1), survival (>= 3.7), survminer (>= 0.4.9), grid, stats |
| System Requirements | |
| URL | https://github.com/pliu55/MPAC |
| Bug Reports | https://github.com/pliu55/MPAC/issues |
See More
| Suggests | rmarkdown, knitr, svglite, bookdown (>= 0.34), testthat (>= 3.0.0) |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | MPAC_1.6.0.tar.gz |
| Windows Binary (x86_64) | MPAC_1.5.0.zip |
| macOS Binary (big-sur-x86_64) | MPAC_1.6.0.tgz |
| macOS Binary (sonoma-arm64) | MPAC_1.6.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/MPAC |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/MPAC |
| Package Short Url | https://bioconductor.org/packages/MPAC/ |
| Package Downloads Report | Download Stats |