Bioconductor 3.22 Released

MesKit

This is the development version of MesKit; for the stable release version, see MesKit.

A tool kit for dissecting cancer evolution from multi-region derived tumor biopsies via somatic alterations


Bioconductor version: Development (3.23)

MesKit provides commonly used analysis and visualization modules based on mutational data generated by multi-region sequencing (MRS). This package allows to depict mutational profiles, measure heterogeneity within or between tumors from the same patient, track evolutionary dynamics, as well as characterize mutational patterns on different levels. Shiny application was also developed for a need of GUI-based analysis. As a handy tool, MesKit can facilitate the interpretation of tumor heterogeneity and the understanding of evolutionary relationship between regions in MRS study.

Author: Mengni Liu [aut, cre] ORCID iD ORCID: 0000-0001-9938-9973 , Jianyu Chen [aut, ctb] ORCID iD ORCID: 0000-0003-4491-9265 , Xin Wang [aut, ctb] ORCID iD ORCID: 0000-0002-6072-599X

Maintainer: Mengni Liu <niinleslie at gmail.com>

Citation (from within R, enter citation("MesKit")):

Installation

To install this package, start R (version "4.6") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("MesKit")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews Software
Version 1.21.0
In Bioconductor since BioC 3.12 (R-4.0) (5 years)
License GPL-3
Depends R (>= 4.0.0)
Imports methods, data.table, Biostrings, dplyr, tidyr (>= 1.0.0), ape (>= 5.4.1), ggrepel, pracma, ggridges, AnnotationDbi, IRanges, circlize, cowplot, mclust, phangorn, ComplexHeatmap(>= 1.9.3), ggplot2, RColorBrewer, grDevices, stats, utils, S4Vectors
System Requirements
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Suggests shiny, knitr, rmarkdown, BSgenome.Hsapiens.UCSC.hg19 (>= 1.4.0), org.Hs.eg.db, clusterProfiler, TxDb.Hsapiens.UCSC.hg19.knownGene
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Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/MesKit
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MesKit
Package Short Url https://bioconductor.org/packages/MesKit/
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