Journal
NATURE COMMUNICATIONS
Volume 11, Issue 1, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/s41467-020-15816-6
Keywords
-
Categories
Funding
- National Institutes of Health (NIH) [HL-095056, HL-28481, U01 DK105561]
- Academy of Finland [272376, 266286, 314383, 315035]
- Finnish Medical Foundation
- Finnish Diabetes Research Foundation
- Novo Nordisk Foundation
- Gyllenberg Foundation
- Sigrid Juselius Foundation
- Helsinki University Hospital Research Funds
- University of Helsinki
- NIA [P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, U01AG61356]
- Illinois Department of Public Health
- Translational Genomics Research Institute
- National Science Foundation Graduate Research Fellowship Program [DGE-1650604]
- HHMI Gilliam fellowship
- AHA Grant [19PRE34430112]
- NIH/NHLBI F31 fellowship [HL142180]
- National Science Foundation [1705197]
- NIH/NHGRI [HG010505-02]
Ask authors/readers for more resources
We present Bisque, a tool for estimating cell type proportions in bulk expression. Bisque implements a regression-based approach that utilizes single-cell RNA-seq (scRNA-seq) or single-nucleus RNA-seq (snRNA-seq) data to generate a reference expression profile and learn gene-specific bulk expression transformations to robustly decompose RNA-seq data. These transformations significantly improve decomposition performance compared to existing methods when there is significant technical variation in the generation of the reference profile and observed bulk expression. Importantly, compared to existing methods, our approach is extremely efficient, making it suitable for the analysis of large genomic datasets that are becoming ubiquitous. When applied to subcutaneous adipose and dorsolateral prefrontal cortex expression datasets with both bulk RNA-seq and snRNA-seq data, Bisque replicates previously reported associations between cell type proportions and measured phenotypes across abundant and rare cell types. We further propose an additional mode of operation that merely requires a set of known marker genes.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available