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mist

This is thereleased version of mist; for the devel version, seemist.

Differential Methylation Analysis for scDNAm Data

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DOI: 10.18129/B9.bioc.mist


Bioconductor version: Release (3.22)

mist (Methylation Inference for Single-cell along Trajectory) is a hierarchical Bayesian framework for modeling DNA methylation trajectories and performing differential methylation (DM) analysis in single-cell DNA methylation (scDNAm) data. It estimates developmental-stage-specific variations, identifies genomic features with drastic changes along pseudotime, and, for two phenotypic groups, detects features with distinct temporal methylation patterns. mist uses Gibbs sampling to estimate parameters for temporal changes and stage-specific variations.

Author: Daoyu Duan [aut, cre]ORCID iD ORCID: 0000-0002-3147-2006

Maintainer: Daoyu Duan <dxd429 at case.edu>

Citation (from within R, entercitation("mist")):

Installation

To install this package, start R (version "4.5") and enter:

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

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

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("mist")
mist_vignetteHTMLR Script
Reference ManualPDF
NEWSText
LICENSEText

Need some help? Ask on the Bioconductor Support site!

Details

biocViewsDNAMethylation,DifferentialMethylation,Epigenetics,SingleCell,Software
Version1.2.0
In Bioconductor sinceBioC 3.21 (R-4.5) (0.5 years)
LicenseMIT + fileLICENSE
DependsR (>= 4.5.0)
ImportsBiocParallel,MCMCpack,Matrix,S4Vectors, methods,rtracklayer,car,mvtnorm,SummarizedExperiment,SingleCellExperiment,BiocGenerics, stats,rlang
System Requirements
URLhttps://https://github.com/dxd429/mist
Bug Reportshttps://https://github.com/dxd429/mist/issues
See More
Suggestsknitr,rmarkdown,RUnit,ggplot2,BiocStyle
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Build ReportBuild Report

Package Archives

FollowInstallation instructions to use this package in your R session.

Source Packagemist_1.2.0.tar.gz
Windows Binary (x86_64) mist_1.2.0.zip
macOS Binary (x86_64)mist_1.2.0.tgz
macOS Binary (arm64)mist_1.2.0.tgz
Source Repositorygit clone https://git.bioconductor.org/packages/mist
Source Repository (Developer Access)git clone git@git.bioconductor.org:packages/mist
Bioc Package Browserhttps://code.bioconductor.org/browse/mist/
Package Short Urlhttps://bioconductor.org/packages/mist/
Package Downloads ReportDownload Stats

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