Evidence map›Paper›PMID 37645732›Full record

ArticlebioRxiv : the preprint server for biology2023

Voyager: exploratory single-cell genomics data analysis with geospatial statistics.

Lambda Moses, Pétur Helgi Einarsson, Kayla Jackson, Laura Luebbert, A Sina Booeshaghi, Sindri Antonsson, Nicolas Bray, Páll Melsted, Lior Pachter

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. 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, 55 citations in OpenAlex.

  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

9 authors at 2 institutions in 2 countries.

Lambda MosesDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
Pétur Helgi EinarssonFaculty of Industrial Engineering, Mechanical Engineering and Computer Science, Reykjavík, Iceland.
Kayla JacksonDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
Laura LuebbertDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
A Sina BooeshaghiDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
Sindri AntonssonFaculty of Industrial Engineering, Mechanical Engineering and Computer Science, Reykjavík, Iceland.
Nicolas BrayBoston, MA.
Páll MelstedFaculty of Industrial Engineering, Mechanical Engineering and Computer Science, Reykjavík, Iceland.
Lior PachterDivision of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
California Institute of Technology · USUniversity of Iceland · IS

Funding

Center for Mouse Genomic Variation at Single Cell ResolutionUM1HG012077 · NHGRI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Seyed Ali Mortazavi, BARBARA J WOLD · 2021 to 2026
$13.7M
NHGRI NIH HHS UM1 HG012077
6 · The paper itself

Abstract

Exploratory spatial data analysis (ESDA) can be a powerful approach to understanding single-cell genomics datasets, but it is not yet part of standard data analysis workflows. In particular, geospatial analyses, which have been developed and refined for decades, have yet to be fully adapted and applied to spatial single-cell analysis. We introduce the Voyager platform, which systematically brings the geospatial ESDA tradition to (spatial) -omics, with local, bivariate, and multivariate spatial methods not yet commonly applied to spatial -omics, united by a uniform user interface. Using Voyager, we showcase biological insights that can be derived with its methods, such as biologically relevant negative spatial autocorrelation. Underlying Voyager is the SpatialFeatureExperiment data structure, which combines Simple Feature with SingleCellExperiment and AnnData to represent and operate on geometries bundled with gene expression data. Voyager has comprehensive tutorials demonstrating ESDA built on GitHub Actions to ensure reproducibility and scalability, using data from popular commercial technologies. Voyager is implemented in both R/Bioconductor and Python/PyPI, and features compatibility tests to ensure that both implementations return consistent results.

Identifiers

PMID37645732
PMCPMC10461913
OpenAlexW4385174515

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.