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MesKit

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

Bioconductor version: Release (3.17)

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] , Jianyu Chen [aut, ctb] , Xin Wang [aut, ctb]

Maintainer: Mengni Liu <niinleslie at gmail.com>

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

Installation

To install this package, start R (version "4.3") and enter:

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

BiocManager::install("MesKit")

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("MesKit")
Analyze and Visualize Multi-region Whole-exome Sequencing Data HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews Software
Version 1.10.0
In Bioconductor since BioC 3.12 (R-4.0) (3 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
Linking To
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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Package Archives

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

Source Package MesKit_1.10.0.tar.gz
Windows Binary MesKit_1.10.0.zip
macOS Binary (x86_64) MesKit_1.10.0.tgz
macOS Binary (arm64) MesKit_1.10.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/MesKit
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MesKit
Bioc Package Browser https://code.bioconductor.org/browse/MesKit/
Package Short Url https://bioconductor.org/packages/MesKit/
Package Downloads Report Download Stats