Evidence map›Paper›PMID 42342707›Full record

ArticleScientific data2026

Persistent hindrances to data re-use in single-cell genomics.

Sanja Rogic, Xinrui Xiang Yu, Brianna Xu, Alexandra Millett, Salva Sherif, Guillaume Poirier-Morency, Rachel Schwartz, Paul Pavlidis

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Sanja RogicMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
Xinrui Xiang YuMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
Brianna XuMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
Alexandra MillettMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
Salva SherifMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
Guillaume Poirier-MorencyMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
Rachel SchwartzMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
Paul PavlidisMichael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada. paul@msl.ubc.ca.

Funding

Neuroinformatics for gene expression: networks, function and meta-analysisR01MH111099 · NIMH · UNIVERSITY OF BRITISH COLUMBIA · PI PAVLIDIS, PAUL · 2016 to 2025
$3.6M
Natural Sciences and Engineering Research Council of Canada RGPIN-2016-05991NIH HHS MH111099NIMH NIH HHS R01 MH111099
6 · The paper itself

Abstract

We evaluated the reusability of publicly available single-cell RNA-sequencing studies (scRNA-seq) from the Gene Expression Omnibus, focusing on the prevalent 10x Genomics-based datasets. Through semi-automated and manual curation, we assessed the availability of cell-level expression count matrices and cell-type annotations. Only around 40% of studies provided readily usable processed count data that could be reliably mapped to GEO metadata, and fewer than 10% included author-provided cell-type labels. Although most studies had raw sequencing files available, few could be re-analyzed automatically without reliance on heuristics. Our findings show that existing practices for scRNA-seq data distribution and sharing are insufficient for effective reuse, and highlight the urgent need for repositories to strengthen and enforce submission requirements, particularly for processed data and cell-type annotations.

Indexed as

GenomicsSingle-Cell AnalysisSequence Analysis, RNASingle-Cell Gene Expression Analysis

Identifiers

PMID42342707
PMCPMC13677686

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.