DeconvoBuddies

The goal of DeconvoBuddies is to provide helper functions for the deconvolution process, as well as a paired dataset designed to test the performance of deconvolution arguments. The dataset is from Human DLPFC, and contains bulk RNA-seq, single nucleus RNA-seq, and estimated cell type proportions from RNAScope/IF.

Installation instructions

Get the latest stable R release from CRAN. Then install DeconvoBuddies using from Bioconductor the following code:

if (!requireNamespace("BiocManager", quietly = TRUE)) {
    install.packages("BiocManager")
}

BiocManager::install("DeconvoBuddies")

And the development version from GitHub with:

BiocManager::install("LieberInstitute/DeconvoBuddies")

Application of DeconvoBuddies

Access Datasets

DeconvoBuddies contains paired snRNA-seq, bulk RNA-seq, and cell type proportion data from the human DLPFC from this study.

## Access data with fetch_deconvo_data
sce_DLPFC_example <- fetch_deconvo_data("sce_DLPFC_example")
#> 2024-10-10 14:34:01.837653 loading file /Users/louise.huuki/Library/Caches/org.R-project.R/R/BiocFileCache/fd1c5d42efb7_sce_DLPFC_example.Rdata%3Frlkey%3Dv3z4u8ru0d2y12zgdl1az07q9%26st%3D1dcfqc1i%26dl%3D1

## explore the single cell experiment object
sce_DLPFC_example
#> class: SingleCellExperiment 
#> dim: 557 10000 
#> metadata(3): Samples cell_type_colors cell_type_colors_broad
#> assays(1): logcounts
#> rownames(557): GABRD PRDM16 ... AFF2 MAMLD1
#> rowData names(7): source type ... gene_type binomial_deviance
#> colnames(10000): 8_AGTGACTGTAGTTACC-1 17_GCAGCCAGTGAGTCAG-1 ...
#>   12_GGACGTCTCTGACAGT-1 1_GGTTAACTCTCTCTAA-1
#> colData names(32): Sample Barcode ... cellType_layer layer_annotation
#> reducedDimNames(0):
#> mainExpName: NULL
#> altExpNames(0):

Find Marker Genes and Visualize Expression

DeconvoBuddies has tools for finding marker genes ideal for deconvolution, and plotting functions to quickly visualize the expression of selected genes in a snRNA-seq data.

Plot Deconvoltion Cell Type Proportions

Create composition bar plots of predicted cell type proportions.

Citation

Below is the citation output from using citation('DeconvoBuddies') in R. Please run this yourself to check for any updates on how to cite DeconvoBuddies.

print(citation("DeconvoBuddies"), bibtex = TRUE)
#> To cite package 'DeconvoBuddies' in publications use:
#> 
#>   Huuki-Myers LA, Maynard KR, Hicks SC, Zandi P, Kleinman JE, Hyde TM,
#>   Goes FS, Collado-Torres L (2024). _DeconvoBuddies: a R/Bioconductor
#>   package with deconvolution helper functions_.
#>   doi:10.18129/B9.bioc.DeconvoBuddies
#>   <https://doi.org/10.18129/B9.bioc.DeconvoBuddies>,
#>   https://github.com/LieberInstitute/DeconvoBuddies/DeconvoBuddies - R
#>   package version 0.99.0,
#>   <http://www.bioconductor.org/packages/DeconvoBuddies>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {DeconvoBuddies: a R/Bioconductor package with deconvolution helper functions},
#>     author = {Louise A. Huuki-Myers and Kristen R. Maynard and Stephanie C. Hicks and Peter Zandi and Joel E. Kleinman and Tom M. Hyde and Fernando S. Goes and Leonardo Collado-Torres},
#>     year = {2024},
#>     url = {http://www.bioconductor.org/packages/DeconvoBuddies},
#>     note = {https://github.com/LieberInstitute/DeconvoBuddies/DeconvoBuddies - R package version 0.99.0},
#>     doi = {10.18129/B9.bioc.DeconvoBuddies},
#>   }
#> 
#>   Huuki-Myers LA, Montgomery KD, Kwon SH, Cinquemani S, Eagles NJ,
#>   Gonzalez-Padilla D, Maden SK, Kleinman JE, Hyde TM, Hicks SC, Maynard
#>   KR, Collado-Torres L (2024). "Benchmark of cellular deconvolution
#>   methods using a multi-assay reference dataset from postmortem human
#>   prefrontal cortex." _bioRxiv_. doi:10.1101/2024.02.09.579665
#>   <https://doi.org/10.1101/2024.02.09.579665>,
#>   <https://doi.org/10.1101/2024.02.09.579665>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Article{,
#>     title = {Benchmark of cellular deconvolution methods using a multi-assay reference dataset from postmortem human prefrontal cortex},
#>     author = {Louise A. Huuki-Myers and Kelsey D. Montgomery and Sang Ho Kwon and Sophia Cinquemani and Nicholas J. Eagles and Daianna Gonzalez-Padilla and Sean K. Maden and Joel E. Kleinman and Thomas M. Hyde and Stephanie C. Hicks and Kristen R. Maynard and Leonardo Collado-Torres},
#>     year = {2024},
#>     journal = {bioRxiv},
#>     doi = {10.1101/2024.02.09.579665},
#>     url = {https://doi.org/10.1101/2024.02.09.579665},
#>   }

Please note that the DeconvoBuddies was only made possible thanks to many other R and bioinformatics software authors, which are cited either in the vignettes and/or the paper(s) describing this package.

Code of Conduct

Please note that the DeconvoBuddies project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

Development tools

Continuous code testing is possible thanks to GitHub actions through usethis, remotes, and rcmdcheck customized to use Bioconductor’s docker containers and BiocCheck.
Code coverage assessment is possible thanks to codecov and covr.
The documentation website is automatically updated thanks to pkgdown.
The code is styled automatically thanks to styler.
The documentation is formatted thanks to devtools and roxygen2.

For more details, check the dev directory.

This package was developed using biocthis.

This package is submitted to Bioconductor

LieberInstitute / DeconvoBuddies

readme