MPAC
Multi-omic Pathway Analysis of Cells
Bioconductor version: 3.23 · Package version: 1.6.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("MPAC") Details
| Maintainer | Peng Liu <pliu55.wisc+bioconductor@gmail.com> |
| Author | Peng Liu [aut, cre] (ORCID: <https://orcid.org/0000-0001-5655-2259>), Paul Ahlquist [aut], Irene Ong [aut], Anthony Gitter [aut] |
| License | GPL-3 |
| URL | https://github.com/pliu55/MPAC |
| Bug Reports | https://github.com/pliu55/MPAC/issues |
| Downloads rank | 151 |
| Source branch | RELEASE_3_23 |
| biocViews | Clustering, ImmunoOncology, RNASeq, Sequencing, Software, Survival, Technology |
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Dependencies
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
Suggests: rmarkdown, knitr, svglite, bookdown (>= 0.34), testthat (>= 3.0.0)