ArticleBriefings in bioinformatics2022
DURIAN: an integrative deconvolution and imputation method for robust signaling analysis of single-cell transcriptomics data.
Article in Briefings in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A comparison of integration methods for single-cell RNA sequencing data and ATAC sequencing data.Quantitative biology (Beijing, China) · 2025Review
- Integration of unpaired single cell omics data by deep transfer graph convolutional network.PLoS computational biology · 2025Article
- scRNMF: An imputation method for single-cell RNA-seq data by robust and non-negative matrix factorization.PLoS computational biology · 2024Article
- The diversification of methods for studying cell-cell interactions and communication.Nature reviews. Genetics · 2024Review
- [Imputation method for dropout in single-cell transcriptome data].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2023Review
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Authors and funding
3 authors.
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Abstract
Single-cell RNA sequencing trades read-depth for dimensionality, often leading to loss of critical signaling gene information that is typically present in bulk data sets. We introduce DURIAN (Deconvolution and mUltitask-Regression-based ImputAtioN), an integrative method for recovery of gene expression in single-cell data. Through systematic benchmarking, we demonstrate the accuracy, robustness and empirical convergence of DURIAN using both synthetic and published data sets. We show that use of DURIAN improves single-cell clustering, low-dimensional embedding, and recovery of intercellular signaling networks. Our study resolves several inconsistent results of cell-cell communication analysis using single-cell or bulk data independently. The method has broad application in biomarker discovery and cell signaling analysis using single-cell transcriptomics data sets.
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