Evidence map›Paper›PMID 38273415›Full record

ArticleGenome biology2024

Gene panel selection for targeted spatial transcriptomics.

Yida Zhang, Viktor Petukhov, Evan Biederstedt, Richard Que, Kun Zhang, Peter V Kharchenko

Abstract read
In one paragraph

Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  16. Review
  17. Mapping Human Tissues with Highly Multiplexed RNA in situ Hybridization.bioRxiv : the preprint server for biology · 2023
    Article
  18. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Yida ZhangDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Viktor PetukhovDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Evan BiederstedtDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Richard QueDepartment of Bioengineering, University of California San Diego, La Jolla, CA, USA.
Kun ZhangDepartment of Bioengineering, University of California San Diego, La Jolla, CA, USA.
Peter V KharchenkoDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. peter.kharchenko@post.harvard.edu.ORCID 0000-0002-6036-5875

Funding

Kidney single cell and spatial molecular atlas project - KIDSSMAPU54DK134301 · NIDDK · WASHINGTON UNIVERSITY · PI JAIN, SANJAY · 2022 to 2025
$7.8M
Organ Specific ProjectU54HL145608 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HAGOOD, JAMES S., JAIN, SANJAY · 2018 to 2021
$5.6M
Single cell multiomic and spatial atlas of acute and chronic kidney injuryU01DK114933 · NIDDK · WASHINGTON UNIVERSITY · PI Sanjay Jain · 2022 to 2026
$5.0M
NHLBI NIH HHS U54 HL145608NIDDK NIH HHS U01 DK114933NIDDK NIH HHS U54 DK134301NIH HHS 5U54HL145608
6 · The paper itself

Abstract

Targeted spatial transcriptomics hold particular promise in analyzing complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is their reliance on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method performing gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.

Indexed as

Gene Expression ProfilingGenetic TechniquesSequence Analysis, RNASingle-Cell AnalysisTranscriptomeCell type hierarchyGene panel selectionPlatform effectSingle-cell RNA sequencingTargeted spatial transcriptomics

Identifiers

PMID38273415
PMCPMC10811939

What OpenQuestion holds

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LicenceCC BY
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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.