Evidence map›Paper›PMID 39152991›Full record

ArticleBioinformatics (Oxford, England)2024

SpatialOne: end-to-end analysis of visium data at scale.

Mena Kamel, Amrut Sarangi, Pavel Senin, Sergio Villordo, Mathew Sunaal, Het Barot, Seqian Wang, Ana Solbas, Luis Cano, Marion Classe and 2 more

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2024. 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. Article
  2. Cancer therapy resistance from a spatial-omics perspective.Clinical and translational medicine · 2025
    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

12 authors.

Mena KamelDigital R&D, Sanofi, Paris 75017, France.ORCID 0009-0007-1380-6950
Amrut SarangiDigital R&D, Sanofi, Paris 75017, France.
Pavel SeninDigital R&D, Sanofi, Paris 75017, France.ORCID 0000-0001-5517-7768
Sergio VillordoDigital R&D, Sanofi, Paris 75017, France.
Mathew SunaalDigital R&D, Sanofi, Paris 75017, France.
Het BarotDigital R&D, Sanofi, Paris 75017, France.
Seqian WangDigital R&D, Sanofi, Paris 75017, France.
Ana SolbasDigital R&D, Sanofi, Paris 75017, France.
Luis CanoPrecision Medicine & Computational Biology, Sanofi, Vitry-sur-Seine 94400, France.
Marion ClassePrecision Medicine & Computational Biology, Sanofi, Vitry-sur-Seine 94400, France.ORCID 0000-0002-0802-6585
Ziv Bar-JosephDigital R&D, Sanofi, Water Street 450, Cambridge, MA 02141, USA.ORCID 0000-0003-3430-6051
Albert Pla PlanasDigital R&D, Sanofi, Carrer de Rosselló i Porcel 21, Barcelona 08016, Spain.ORCID 0000-0001-7527-2500

Funding

Sanofi Digital
6 · The paper itself

Abstract

motivationSpatial transcriptomics allow to quantify mRNA expression within the spatial context. Nonetheless, in-depth analysis of spatial transcriptomics data remains challenging and difficult to scale due to the number of methods and libraries required for that purpose.

resultsHere we present SpatialOne, an end-to-end pipeline designed to simplify the analysis of 10x Visium data by combining multiple state-of-the-art computational methods to segment, deconvolve, and quantify spatial information; this approach streamlines the analysis of reproducible spatial-data at scale. AVAILABILITY AND IMPLEMENTATION: SpatialOne source code and execution examples are available at https://github.com/Sanofi-Public/spatialone-pipeline, experimental data is available at https://zenodo.org/records/12605154. SpatialOne is distributed as a docker container image.

Indexed as

SoftwareComputational BiologyGene Expression ProfilingRNA, MessengerTranscriptomeRNA, Messenger

Identifiers

PMID39152991
PMCPMC11374018

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.