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https://github.com/cozygene/bisque

An R toolkit for estimation of cell composition from bulk expression data
https://github.com/cozygene/bisque

Last synced: 17 days ago
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An R toolkit for estimation of cell composition from bulk expression data

Host: GitHub
URL: https://github.com/cozygene/bisque
Owner: cozygene
Created: 2019-03-19T21:34:54.000Z (over 5 years ago)
Default Branch: master
Last Pushed: 2021-08-11T13:10:05.000Z (almost 3 years ago)
Last Synced: 2024-02-28T21:30:59.822Z (4 months ago)
Language: R
Homepage:
Size: 118 KB
Stars: 65
Watchers: 4
Forks: 20
Open Issues: 8
Metadata Files:
- Readme: README.md

Lists

awesome-deconvolution - Bisque - cell information ([Jew et al 2020](https://www.nature.com/articles/s41467-020-15816-6); tags: single-cell; transcriptomics; rna-seq; bulk). (Methods)

README

# Bisque

[![Build Status](https://travis-ci.org/cozygene/bisque.svg?branch=master)](https://travis-ci.org/cozygene/bisque)
[![codecov](https://codecov.io/gh/cozygene/bisque/branch/master/graph/badge.svg)](https://codecov.io/gh/cozygene/bisque)
[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/r-bisquerna/README.html)
[![CRAN Version](https://www.r-pkg.org/badges/version/BisqueRNA)](https://CRAN.R-project.org/package=BisqueRNA)

An R toolkit for accurate and efficient estimation of cell composition ('decomposition') from bulk expression data with single-cell information.

Bisque provides two modes of operation:

### Reference-based decomposition
This method utilizes single-cell data to decompose bulk expression.
We assume that both single-cell and bulk counts are measured from the same tissue.
Specifically, the cell composition of the labeled single-cell data should match the expected physiological composition.
While we don't explicitly require matched samples, we expect having samples with both single-cell and bulk expression measured will provide more accurate results.

### Marker-based decomposition
This method utilizes marker genes alone to decompose bulk expression when a reference profile is not available.
Single-cell data is not explicitly required but can be used to identify these marker genes.
This method captures relative abundances of a cell type across individuals. Note that these abundances are not proportions, so they cannot be compared between different cell types.

## Installation

The Bisque R package is available on CRAN
```r
install.packages("BisqueRNA")
```

as well as Bioconda
```
conda install r-bisquerna
```

The package can also be installed from the GitHub repository
```r
devtools::install_github("cozygene/bisque")
```

## Getting Started
You can load Bisque as follows:

```r
library(BisqueRNA)
```

The two modes of operation described above are called as follows:

```r
res <- BisqueRNA::ReferenceBasedDecomposition(bulk.eset, sc.eset, markers)
```

```r
res <- BisqueRNA::MarkerBasedDecomposition(bulk.eset, markers)
```

Each method returns a list of results with estimated cell proportions/abundances stored in `res$bulk.props`.

To see examples of these methods on simulated data, check out the vignette:

```r
browseVignettes("BisqueRNA")
```