Individual-level expression deconvolution and assessment of cross-sample variation

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.

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BibTeX RIS

BibTeX

@misc{kang2026individuallevel,
  title = {{Individual-level expression deconvolution and assessment of cross-sample variation}},
  author = {K. Kang and K. Xie},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.14.751599},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.14.751599v1},
  note = {CC BY},
}

RIS

TY  - UNPB
TI  - Individual-level expression deconvolution and assessment of cross-sample variation
AU  - K. Kang
AU  - K. Xie
PY  - 2026
DA  - 2026/09/14
PB  - bioRxiv
DO  - 10.64898/2026.09.14.751599
UR  - https://www.biorxiv.org/content/10.64898/2026.09.14.751599v1
AB  - 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.
ER  -

Abstract

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