Evidence map›Paper›PMID 36945384›Full record

ArticlebioRxiv : the preprint server for biology2023

Torch-eCpG: A fast and scalable eQTM mapper for thousands of molecular phenotypes with graphical processing units.

Kord M Kober, Liam Berger, Ritu Roy, Adam Olshen

Abstract 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. 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
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Kord M KoberSchool of Nursing, University of California San Francisco, San Francisco, California, USA.
Liam BergerSchool of Nursing, University of California San Francisco, San Francisco, California, USA.
Ritu RoySchool of Nursing, University of California San Francisco, San Francisco, California, USA.
Adam OlshenHelen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, USA.

Funding

Translational InformaticsP30CA082103 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Kate Taylor Shumate · 1999 to 2026
$209.7M
An Investigation of the Molecular Mechanisms for and Prediction of the Severity of Cancer Chemotherapy-Related Fatigue Using a Multi-staged Integrated Omics ApproachR37CA233774 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KOBER, KORD MICHAEL · 2019 to 2025
$4.8M
NCI NIH HHS P30 CA082103NCI NIH HHS R37 CA233774
6 · The paper itself

Abstract

Background: Gene expression may be regulated by the DNA methylation of regulatory elements in Results: We demonstrate the analyses using the tool are reproducible, up to 18x faster using the GPU, and scale linearly with increasing methylation loci. Conclusions: Torch-eCpG is a fast, reliable, and scalable tool to perform eQTM mapping. Source code for Torch-eCpG is available at https://github.com/kordk/torch-ecpg.

Indexed as

DNA methylationeCpGeQTMexpression quantitative trait methylationgene expressionGPUtensortranscriptional regulation

Identifiers

PMID36945384
PMCPMC10028892

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.