In one paragraphArticle in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
34 authors.
Boyi GuoDivision of Biostatistics, Department of Population Health Sciences, University of Utah, Salt Lake City, UT, United States.ORCID 0000-0003-2950-2349 Mengbo LiBioinformatics and Computational Biology Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.ORCID 0000-0002-9666-5810 Alexandru MahmoudChanning Division of Network Medicine, Mass General Brigham, Boston, MA, United States.ORCID 0000-0002-3779-492X Artür ManukyanBerlin Institute for Medical Systems Biology, Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.ORCID 0000-0002-0441-9517 Pratibha PanwarSchool of Mathematics and Statistics, The University of Sydney, Camperdown, NSW, Australia.ORCID 0000-0002-7437-7084 Shreya RaoSchool of Mathematics and Statistics, The University of Sydney, Camperdown, NSW, Australia.ORCID 0009-0007-8140-6844 Callum J SargeantBioinformatics and Computational Biology Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.ORCID 0009-0006-8919-608X Marcel RamosInstitute for Implementation Science in Population Health, City University of New York Graduate School of Public Health and Health Policy, New York, NY, United States.ORCID 0000-0002-3242-0582 Michael TottyDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-9292-8556 Vincent J CareyChanning Division of Network Medicine, Mass General Brigham, Boston, MA, United States.ORCID 0000-0003-4046-0063 Yunshun ChenBioinformatics and Computational Biology Division, Walter and Eliza Hall Institute of Medical Research, Parkville, VIC, Australia.ORCID 0000-0003-4911-5653 Leonardo Collado-TorresDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-2140-308X Shila GhazanfarSchool of Mathematics and Statistics, The University of Sydney, Camperdown, NSW, Australia.ORCID 0000-0001-7861-6997 Kasper D HansenDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0003-0086-0687 Keri MartinowichLieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, United States.ORCID 0000-0002-5237-0789 Kristen R MaynardLieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, United States.ORCID 0000-0003-0031-8468 Ellis PatrickSchool of Mathematics and Statistics, The University of Sydney, Camperdown, NSW, Australia.ORCID 0000-0002-5253-4747 Dario RighelliDepartment of Electrical Engineer and Information Technology, University of Naples "Federico II", Naples, Italy.ORCID 0000-0003-1504-3583 Levi WaldronInstitute for Implementation Science in Population Health, City University of New York Graduate School of Public Health and Health Policy, New York, NY, United States.ORCID 0000-0003-2725-0694 Raphael GottardoBiomedical Data Science Center, Lausanne University Hospital, Lausanne, Switzerland.ORCID 0000-0002-3867-0232 Stephanie C HicksDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States.ORCID 0000-0002-7858-0231 Lukas M WeberDepartment of Biostatistics, Boston University School of Public Health, Boston, MA, United States.ORCID 0000-0002-3282-1730 Funding
Supplement: Enhancing Community Contributions to Bioconductor With Build System Containerization and a GPU for TestingU24HG004059 · NHGRI · DANA-FARBER CANCER INST · PI VINCENT JAMES CAREY, Rafael Angel Irizarry · 2021 to 2026
$7.3MLaminar dissection of cortical human brain gene expression in neuropsychiatric disordersR01MH126393 · NIMH · LIEBER INSTITUTE, INC. · PI MARTINOWICH, KERI · 2021 to 2025
$3.9MSpatial registration of gene expression in the human brainU01MH122849 · NIMH · LIEBER INSTITUTE, INC. · PI MARTINOWICH, KERI · 2020 to 2021
$1.7MComputational Methods for Emerging Spatially-resolved Transcriptomics with Multiple SamplesR35GM150671 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Stephanie Carinne Hicks · 2023 to 2026
$1.2MUnsupervised Statistical Methods for Data-driven Analyses in Spatially Resolved Transcriptomics DataR00HG012229 · NHGRI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Lukas Martin Weber · 2024 to 2026
$730kNHGRI NIH HHS R00 HG012229NHGRI NIH HHS U24 HG004059NIGMS NIH HHS R35 GM150671NIMH NIH HHS R01 MH126393NIMH NIH HHS U01 MH122849
6 · The paper itselfAbstract
Spatial transcriptomics technologies provide spatially-resolved measurements of gene expression through assays that can either target selected genes or capture transcriptome-wide expression profiles. The complexity and variability of these technologies and their associated data necessitate multi-step workflows integrating diverse computational methods and software packages. We provide a freely accessible, open-source, continuously updated and tested online book containing reproducible code examples, datasets, and discussion about data analysis workflows for spatial omics data using Bioconductor in R, including interoperability with Python.
Indexed as
Bioconductorcomputational biologydata analysisgene expressionhigh-dimensional datainteroperabilityopen-sourceRreproducible researchspatially-resolved transcriptomicsspatial omicsspatial transcriptomicsworkflow
Identifiers
PMID41332620
PMCPMC12667768
What OpenQuestion holds
Textmetadata
LicenceCC BY
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