Evidence map›Paper›PMID 42793120›Full record

ArticleBiomolecules2026

scFlowReport: A Reproducible Workflow for Comparative Downstream Biological Analysis of Single-Cell RNA-seq Data.

Nayoung Park, Hyewon Lee, Jaebum Kim

Abstract read
In one paragraph

Article in Biomolecules, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Nayoung ParkDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0003-2722-0639
Hyewon LeeDepartment of Cardiology, Medical Research Institute, Pusan National University Hospital, Busan 49241, Republic of Korea.
Jaebum KimDepartment of Biomedical Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea.ORCID 0000-0002-2287-9760

Funding

Ministry of Education (MOE) and the Seoul Metropolitan Government 2026-ANCHOR-01-001-04Ministry of Science and ICT RS-2024-00407469Ministry of Science and ICT RS-2026-25469184Ministry of Science and ICT RS-2026-25555206
6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) studies are frequently organized around comparisons-disease versus control, treatment response, or genetic perturbation-yet biological interpretation still depends on integrating multiple independent downstream analyses for differential expression, functional enrichment, regulatory network inference, and cell-cell communication analysis. Applying these tools consistently across comparisons typically requires substantial custom scripting, and their heterogeneous outputs must be manually harmonized before the results can be compared or reported together. We present scFlowReport, a lightweight, configuration-driven workflow that propagates a single user-defined comparison across cell-level and sample-aware pseudobulk differential expression, over-representation and ranked functional enrichment, transcription-factor regulon export for SCENIC, and group-resolved LIANA cell-cell communication analysis, starting from an already annotated Seurat object. The workflow automatically compiles complementary downstream results into standardized figures, summary tables, and a self-contained static HTML report that can be readily inspected and shared without requiring a persistent server. Application of scFlowReport to a publicly available Atopic Dermatitis scRNA-seq dataset demonstrated its utility by enabling researchers to obtain complementary biological evidence from multiple established downstream analyses. By coordinating complementary downstream analyses under a shared comparison framework, scFlowReport provides a practical and reproducible workflow for systematic interpretation of comparative single-cell transcriptomic data.

Indexed as

RNA-SeqSequence Analysis, RNASingle-Cell AnalysisSoftwareGene Expression ProfilingHumansSingle-Cell Gene Expression AnalysisWorkflowcell–cell communicationdifferential expressiongene regulatory networkpipelineSeuratsingle-cell RNA sequencing (scRNA-seq)workflow

Identifiers

PMID42793120
PMCPMC13604200

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.