Clustering-independent estimation of cell abundances in bulk tissues using single-cell RNA-seq data
Year: 2023
Type: dataset
Abstract: ConDecon is a clustering-independent method for inferring the likelihood for each cell in a single-cell dataset to be present in a bulk tissue. This repository contains the raw data of the benchmarking analyses presented in the original publication using the pipeline of Avila-Cobos et al. (10.1038/s41467-020-19015-1). We used this pipeline to evaluate the ability of ConDecon and 17 other deconvolution methods to infer discrete cell type abundances in bulk tissues. The compressed file in this repository contains the synthetic bulk data, ground truth cell type proportions, and the predicted cell type proportions for each method and dataset associated with these analyses. Additional details can be found in the Methods section of the ConDecon publication.
Authors: Aubin, Rachael, Camara, Pablo
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4393487072