https://github.com/kieranrcampbell/mfa

Probabilistic inference of single-cell bifurcations
https://github.com/kieranrcampbell/mfa

bifurcation factor-analysis mixture-modelling single-cell

Last synced: 23 days ago
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Probabilistic inference of single-cell bifurcations

• Host: GitHub
• URL: https://github.com/kieranrcampbell/mfa
• Owner: kieranrcampbell
• Created: 2016-09-26T13:20:29.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2022-03-21T16:43:11.000Z (over 2 years ago)
• Last Synced: 2024-02-24T13:32:23.346Z (4 months ago)
• Topics: bifurcation, factor-analysis, mixture-modelling, single-cell
• Language: R
• Size: 77.1 KB
• Stars: 5
• Watchers: 6
• Forks: 3
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Lists

• awesome_single_cell - mfa - [R] - [Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers](https://wellcomeopenresearch.org/articles/2-19/v1) (Software packages / RNA-seq)
• awesome-single-cell - mfa - [R] - [Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers](https://wellcomeopenresearch.org/articles/2-19/v1) (Software packages / RNA-seq)
• awesome-single-cell - mfa - [R] - [Probabilistic modeling of bifurcations in single-cell gene expression data using a Bayesian mixture of factor analyzers](https://wellcomeopenresearch.org/articles/2-19/v1) (Software packages / RNA-seq)

README

        
## mfa - Bayesian inference of bifurcations in single-cell data

`mfa` is an R package implementing Gibbs sampling for a Bayesian hierarchichal mixture of factor analysers for inference of bifurcations in single-cell data.

[![Build Status](https://travis-ci.org/kieranrcampbell/mfa.svg?branch=master)](https://travis-ci.org/kieranrcampbell/mfa) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.345981.svg)](https://doi.org/10.5281/zenodo.345981)

### Installation

`mfa` may be installed either via Bioconductor (coming soon) or Github:

#### Installation from Bioconductor

```r

if (!requireNamespace("BiocManager", quietly=TRUE))

    install.packages("BiocManager")

BiocManager::install("mfa")

```

#### Installation from Github

```r

devtools::install_github("kieranrcampbell/mfa", build_vignettes = TRUE)

```

### Usage

For a cell-by-gene matrix of expression Y, MFA can be envoked via

```r

m <- mfa(Y)

```

which will perform Gibbs sampling to infer pseudotimes, branch structure, and genes involved in the bifurcation.

For full usage see the package vignette:

```r

vignette('introduction_to_mfa')

```

### Authors

Kieran Campbell & Christopher Yau

University of Oxford