Evidence map›Paper›PMID 37698995›Full record

ArticleBioinformatics (Oxford, England)2023

MoleculeExperiment enables consistent infrastructure for molecule-resolved spatial omics data in bioconductor.

Bárbara Zita Peters Couto, Nicholas Robertson, Ellis Patrick, Shila Ghazanfar

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Orchestrating Spatial Transcriptomics Analysis with Bioconductor.bioRxiv : the preprint server for biology · 2025
    Article
  4. Article
  5. Article
  6. Article
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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

4 authors.

Bárbara Zita Peters CoutoSchool of Mathematics and Statistics, The University of Sydney, Camperdown, NSW 2006, Australia.
Nicholas RobertsonSchool of Mathematics and Statistics, The University of Sydney, Camperdown, NSW 2006, Australia.
Ellis PatrickSchool of Mathematics and Statistics, The University of Sydney, Camperdown, NSW 2006, Australia.ORCID 0000-0002-5253-4747
Shila GhazanfarSchool of Mathematics and Statistics, The University of Sydney, Camperdown, NSW 2006, Australia.ORCID 0000-0001-7861-6997

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationImaging-based spatial transcriptomics (ST) technologies have achieved subcellular resolution, enabling detection of individual molecules in their native tissue context. Data associated with these technologies promise unprecedented opportunity toward understanding cellular and subcellular biology. However, in R/Bioconductor, there is a scarcity of existing computational infrastructure to represent such data, and particularly to summarize and transform it for existing widely adopted computational tools in single-cell transcriptomics analysis, including SingleCellExperiment and SpatialExperiment (SPE) classes. With the emergence of several commercial offerings of imaging-based ST, there is a pressing need to develop consistent data structure standards for these technologies at the individual molecule-level.

resultsTo this end, we have developed MoleculeExperiment, an R/Bioconductor package, which (i) stores molecule and cell segmentation boundary information at the molecule-level, (ii) standardizes this molecule-level information across different imaging-based ST technologies, including 10× Genomics' Xenium, and (iii) streamlines transition from a MoleculeExperiment object to a SpatialExperiment object. Overall, MoleculeExperiment is generally applicable as a data infrastructure class for consistent analysis of molecule-resolved spatial omics data. AVAILABILITY AND IMPLEMENTATION: The MoleculeExperiment package is publicly available on Bioconductor at https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html. Source code is available on Github at: https://github.com/SydneyBioX/MoleculeExperiment. The vignette for MoleculeExperiment can be found at https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html.

Indexed as

Gene Expression ProfilingGenomicsSoftware

Identifiers

PMID37698995
PMCPMC10504467

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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.