CDSeq2 integrates individual-level cell-type expression deconvolution with recoverability-guided prioritization
Abstract
CDSeq2 combines reference-informed Bayesian deconvolution with gene-type prioritization for individual-level expression analysis from bulk RNA sequencing. Brain benchmarks showed accurate RNA-fraction estimates and expression recovery comparable to BayesPrism in excitatory neurons. Prioritization enriched accurately recovered profiles and supported continuous-phenotype and cell-type-specific expression quantitative trait locus (eQTL) analyses, with the strongest application evidence in excitatory neurons. Forty independently generated synthetic cohorts with local linkage disequilibrium evaluated a frozen scorer. In the principal stronger-effect setting, retaining 40% of candidate profiles increased eQTL precision from 77.6% to 92.6%. CDSeq2 delivers complete expression estimates with optional prioritization to support focused biological follow-up.
02 /Specification & Classification
Click any tag to browse matching papers- Citations
- 0
- Organism
- Assay
- Research Focus
- Approach
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Bayesian estimation of cell-type-specific gene expression per bulk sample with prior derived from single-cell data
Jiebiao Wang, Kathryn Roeder, Bernie Devlin·Genome ResearchPeer-reviewed·Oct 1, 2021
- Evaluating performance and applications of sample-wise cell deconvolution methods on human brain transcriptomic data
Rujia Dai, Tianyao Chu, … Chunyu Liu·Science AdvancesPeer-reviewed·May 23, 2024
- Fine-grained deconvolution of cell-type effects from human bulk brain data using a large single-nucleus RNA sequencing based reference panel.
Edwin J. C. G. van den Oord, Karolina A. Åberg·bioRxiv·Jun 23, 2022
- Using multiple measurements of tissue to estimate subject- and cell-type-specific gene expression
Jiebiao Wang, Bernie Devlin, Kathryn Roeder·BioinformaticsPeer-reviewed·Aug 9, 2019
- DEBay: a computational tool for deconvolution of quantitative PCR data for estimation of cell type-specifc gene expression in a mixed population
Vimalathithan Devaraj, Biplab Bose·HeliyonPeer-reviewed·Jul 1, 2020
- A computational method for direct imputation of cell type-specific expression profiles and cellular compositions from bulk-tissue RNA-Seq in brain disorders
Abolfazl Doostparast Torshizi, Jubao Duan, Kai Wang·NAR Genomics and BioinformaticsPeer-reviewed·Apr 9, 2021