BSDE: barycenter single-cell differential expression for case-control studies.
View / Open Files
Publication Date
2022-05-01ISSN
1367-4803
Language
eng
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Zhang, M., & Guo, F. R. (2022). BSDE: barycenter single-cell differential expression for case-control studies.. https://doi.org/10.1093/bioinformatics/btac171
Abstract
<h4>Motivation</h4>Single-cell sequencing brings about a revolutionarily high resolution for finding differentially expressed genes (DEGs) by disentangling highly heterogeneous cell tissues. Yet, such analysis is so far mostly focused on comparing between different cell types from the same individual. As single-cell sequencing becomes cheaper and easier to use, an increasing number of datasets from case-control studies are becoming available, which call for new methods for identifying differential expressions between case and control individuals.<h4>Results</h4>To bridge this gap, we propose barycenter single-cell differential expression (BSDE), a nonparametric method for finding DEGs for case-control studies. Through the use of optimal transportation for aggregating distributions and computing their distances, our method overcomes the restrictive parametric assumptions imposed by standard mixed-effect-modeling approaches. Through simulations, we show that BSDE can accurately detect a variety of differential expressions while maintaining the type-I error at a prescribed level. Further, 1345 and 1568 cell type-specific DEGs are identified by BSDE from datasets on pulmonary fibrosis and multiple sclerosis, among which the top findings are supported by previous results from the literature.<h4>Availability and implementation</h4>R package BSDE is freely available from doi.org/10.5281/zenodo.6332254. For real data analysis with the R package, see doi.org/10.5281/zenodo.6332566. These can also be accessed thorough GitHub at github.com/mqzhanglab/BSDE and github.com/mqzhanglab/BSDE_pipeline. The two single-cell sequencing datasets can be download with UCSC cell browser from cells.ucsc.edu/?ds=ms and cells.ucsc.edu/?ds=lung-pf-control.<h4>Supplementary information</h4>Supplementary data are available at Bioinformatics online.
Keywords
Humans, Case-Control Studies, Software
Identifiers
35561165, PMC9113363
External DOI: https://doi.org/10.1093/bioinformatics/btac171
This record's URL: https://www.repository.cam.ac.uk/handle/1810/338053
Statistics
Total file downloads (since January 2020). For more information on metrics see the
IRUS guide.