Benchmark of cellular deconvolution methods using a multi-assay dataset from postmortem human prefrontal cortex
Cellular deconvolution of bulk RNA-sequencing data using single cell/nuclei RNA-seq reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as the human brain. Here, we generate a multi-assay dataset in postmortem human dorsolateral prefrontal cortex from 22 tissue blocks, including bulk RNA-seq, reference snRNA-seq, and orthogonal measurement of cell type proportions with RNAScope/ImmunoFluorescence. We use this dataset to evaluate six deconvolution algorithms. Bisque and hspe were the most accurate methods. The dataset, as well as the Mean Ratio gene marker finding method, is made available in the DeconvoBuddies R/Bioconductor package.
Authors
- Kelsey D. Montgomery (ORCID: https://orcid.org/0000-0001-8420-0138)
- Louise A. Huuki-Myers (ORCID: https://orcid.org/0000-0001-5148-3602)
- Joel E. Kleinman (ORCID: https://orcid.org/0000-0002-4210-6052)
- Stephanie C. Hicks (ORCID: https://orcid.org/0000-0002-7858-0231)
- Kristen R. Maynard (ORCID: https://orcid.org/0000-0003-0031-8468)
- Nicholas J. Eagles (ORCID: https://orcid.org/0000-0002-9808-5254)
- Thomas M. Hyde (ORCID: https://orcid.org/0000-0002-8746-3037)
- Sang Ho Kwon (ORCID: https://orcid.org/0000-0001-5328-0956)
- Sean K. Maden (ORCID: https://orcid.org/0000-0002-2212-4894)
- Leonardo Collado‐Torres (ORCID: https://orcid.org/0000-0003-2140-308X)
- Daianna González‐Padilla (ORCID: https://orcid.org/0009-0005-8348-3195)
- Sophia Cinquemani (ORCID: https://orcid.org/0000-0001-8640-6375)
Institutions
- Johns Hopkins University (US)
- University of Cambridge (GB)
- Johns Hopkins Medicine (US)
- Behavioral Pharma (United States) (US)
- UK Dementia Research Institute (GB)
- Lieber Institute for Brain Development (US)
Publication Details
- Journal
- Genome biology
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1186/s13059-025-03552-3
- Citations
- 14
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 11.28
Funders
- Lieber Institute for Brain Development
- National Institute of Mental Health