Evidence map›Paper›PMID 41691043›Full record

ReviewCommunications biology2026

A practical guide to targeted single-cell RNA sequencing technologies.

Giulia Moro, Erich Brunner, Konrad Basler

Abstract readReview
In one paragraph

Review in Communications biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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.

Giulia MoroDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland. giulia.moro2@uzh.ch.ORCID http://orcid.org/0000-0002-0642-6294
Erich BrunnerDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0002-9712-9040
Konrad BaslerDepartment of Molecular Life Sciences, University of Zurich, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current single-cell RNA sequencing (scRNA-seq) methods suffer from biases that restrict the detection of cellular transcripts to 10-40% of total RNAs. This hinders the identification of transcripts of interest. Additionally, information retrieved from most high-throughput scRNA-seq methods is confined to untranslated regions toward transcript ends, resulting in loss of detail in internal regions. In this review, we outline biases in scRNA-seq protocol steps that limit transcript and region detection. We then discuss the advantages and disadvantages of targeted sequencing solutions, grouped into five categories according to the protocol step they target. Finally, we present a decision tree that guides researchers in selecting the most suitable targeted method for their experiment.

Indexed as

RNASequence Analysis, RNASingle-Cell AnalysisAnimalsHigh-Throughput Nucleotide SequencingHumansSingle-Cell Gene Expression AnalysisRNA

Identifiers

PMID41691043
PMCPMC12906503

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.