Article

Real-paired single-cell/bulk RNA-seq benchmark and a practical protocol for accurate cell-type deconvolution in human BAL samples

2026-01-14

Abstract excerpt

<h4>Background</h4> Pseudo-bulk RNA-seq, generated by aggregating single-cell profiles, is widely used for benchmarking deconvolution methods because it globally approximates bulk transcriptomes and provides known cell-type proportions as ground truth. However, pseudo-bulk inherits single-cell specific measurement properties, and the extent to which these differ from real bulk RNA-seq remains difficult to quantif...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 2884d121-3c2c-5a88-909a-c09a95191e92
DOI: 10.64898/2026.01.14.699304

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Real-paired single-cell/bulk RNA-seq benchmark and a practical protocol for accurate cell-type deconvolution in human BAL samplesDOI 10.64898/2026.01.14.699304Read

CATD: A reproducible pipeline for selecting cell-type deconvolution methods across tissuesSemantic proximity Read

SCDC: Bulk Gene Expression Deconvolution by Multiple Single-Cell RNA Sequencing ReferencesSemantic proximity Read

Cell-type deconvolution for bulk RNA-seq data using single-cell reference: a comparative analysis and recommendation guidelineSemantic proximity Read

Benchmarking tissue- and cell type-of-origin deconvolution in cell-free transcriptomicsSemantic proximity Read

Effective methods for bulk RNA-Seq deconvolution using scnRNA-Seq transcriptomesSemantic proximity Read

UnBlender: validating individual analyses in respiratory bulk RNA-seq cell type deconvolutionSemantic proximity Read

A standardized atlas of human bronchoalveolar lavage cells built using scalable ensemble annotation and cross-study robust markersSemantic proximity Read

Systematic evaluation of transcriptomics-based deconvolution methods and references using thousands of clinical samplesSemantic proximity Read

MuSiC2: cell type deconvolution for multi-condition bulk RNA-seq dataSemantic proximity Read

Deconer: A comprehensive and systematic evaluation toolkit for reference-based cell type deconvolution algorithms using gene expression dataSemantic proximity Read

Estimating the effect of tissue- and blood-derived cell reference matrices on deconvolving bulk transcriptomic datasetsSemantic proximity Read

IBRAP: Integrated Benchmarking Single-cell RNA-sequencing Analytical PipelineSemantic proximity Read