ArticleiScience2025
Exploring the utility of snRNA-seq in profiling human bladder tissue: A comprehensive comparison with scRNA-seq.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
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.
Who cites it
8 citing papers in PubMed.
- Persistent viral infection in the Drosophila fat body is associated with immune activation at the single cell level.BMC genomics · 2026Article
- Partial domain adaptation enables cross domain cell type annotation between scRNA-seq and snRNA-seq.PLoS computational biology · 2026Article
- Multi-organ single-cell analysis of preferential expression of CAKUT genes.BMC nephrology · 2026Article
- Single-cell profiling defines the cellular landscape of the urinary bladder: a scoping review.European journal of medical research · 2026Review
- Integrated experimental and computational workflows for single-cell transcriptomics in plants.Plant methods · 2026Article
- Writing the Engram: Epigenetic Mechanisms of Memory Allocation.Journal of neurochemistry · 2025Review
- Comparative Transcriptomic Profiling of Corneal Compartments Using Single-Cell and Single-Nucleus Sequencing.Investigative ophthalmology & visual science · 2025Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Single cell sequencing technologies have revolutionized our understanding of biology by mapping cell diversity and gene expression in healthy and diseased tissues. While single-cell RNA sequencing (scRNA-seq) has been widely used, interest in single-nucleus RNA sequencing (snRNA-seq) is growing due to its benefits, including the ability to analyze archival tissues and capture rare cell types that are challenging to dissociate. However, comparative studies across tissues have yielded mixed results, with some reporting enhanced cell type retention using snRNA-seq while others finding cell type identification to be challenging in snRNA-seq data. The GUDMAP consortium aims to construct a molecular atlas of the lower urinary tract (LUT); thus, we set out to determine the strengths and limitations of each approach in characterizing LUT cell types. Using the human bladder, we determined that scRNA-seq offered more discriminative gene sets for identification while snRNA-seq could facilitate capture of previously underrepresented cell types.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.