Evidence map›Paper›PMID 39644148›Full record

ArticleClinical and translational medicine2024

Statistical and computational methods for enabling the clinical and translational application of spatial transcriptomics.

Peijun Wu, Xiang Zhou

Abstract read
In one paragraph

Article in Clinical and translational medicine, 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. 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

2 authors.

Peijun WuDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.ORCID https://orcid.org/0000-0001-9622-8541
Xiang ZhouDepartment of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.ORCID https://orcid.org/0000-0002-4331-7599

Funding

Statistical Methods for Modeling Polygenic Architecture in Association and Re-sequencing StudiesR01HG009124 · NHGRI · YALE UNIVERSITY · PI Xiang Zhou · 2017 to 2026
$3.0M
Develop new bioinformatics infrastructures and computational tools for epitranscriptomics dataR01HG012927 · NHGRI · UNIVERSITY OF CHICAGO · PI Mengjie Chen · 2023 to 2026
$1.6M
Developing new computational tools for spatial transcriptomics dataR01HG011883 · NHGRI · UNIVERSITY OF CHICAGO · PI CHEN, MENGJIE, ZHOU, XIANG · 2021 to 2024
$1.5M
DMS/NIGMS 2: Advanced Statistical Methods for Spatially Resolved Transcriptomics StudiesR01GM144960 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHOU, XIANG · 2021 to 2024
$1.3M
NHGRI NIH HHS R01 HG009124NHGRI NIH HHS R01 HG011883NHGRI NIH HHS R01 HG012927NIGMS NIH HHS R01 GM144960NIH HHS R01GM144960NIH HHS R01HG009124NIH HHS R01HG011883
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Clinical ApplicationsComputational MethodsSpatial TranscriptomicsStatistical Methods

Identifiers

PMID39644148
PMCPMC11624480

What Socratic 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 Socratic graph.