MPAC

Multi-omic Pathway Analysis of Cancer


Bioconductor version: Release (3.20)

Multi-omic Pathway Analysis of Cancer (MPAC), integrates multi-omic data for understanding cancer 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 (from within R, enter citation("MPAC")):

Installation

To install this package, start R (version "4.4") 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 Cancer HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Clustering, ImmunoOncology, RNASeq, Sequencing, Software, Survival, Technology
Version 1.0.0
In Bioconductor since BioC 3.20 (R-4.4) (< 6 months)
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), grid, stats
System Requirements
URL https://github.com/pliu55/MPAC
Bug Reports https://github.com/pliu55/MPAC/issues
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Suggests rmarkdown, knitr, svglite, bookdown (>= 0.34), testthat (>= 3.0.0)
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package MPAC_1.0.0.tar.gz
Windows Binary (x86_64) MPAC_1.0.0.zip (64-bit only)
macOS Binary (x86_64) MPAC_1.0.0.tgz
macOS Binary (arm64) MPAC_0.99.14.tgz
Source Repository git clone https://git.bioconductor.org/packages/MPAC
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MPAC
Bioc Package Browser https://code.bioconductor.org/browse/MPAC/
Package Short Url https://bioconductor.org/packages/MPAC/
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