Evidence map›Paper›PMID 38370654›Full record

ArticlebioRxiv : the preprint server for biology2024

yQTL Pipeline: a structured computational workflow for large scale quantitative trait loci discovery and downstream visualization.

Mengze Li, Zeyuan Song, Anastasia Gurinovich, Nicholas Schork, Paola Sebastiani, Stefano Monti

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Mengze LiBioinformatics Program, Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA.ORCID 0000-0002-5441-9021
Zeyuan SongDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA, USA.
Anastasia GurinovichInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.
Nicholas SchorkQuantitative Medicine and Systems Biology, The Translational Genomics Research Institute, Phoenix, AZ, USA.
Paola SebastianiInstitute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA.
Stefano MontiBioinformatics Program, Faculty of Computing & Data Sciences, Boston University, Boston, MA, USA.ORCID 0000-0002-9376-0660
Boston University · USTufts University · USTranslational Genomics Research Institute · US

Funding

The Long Life Family StudyU19AG063893 · NIA · WASHINGTON UNIVERSITY · PI PAOLA SEBASTIANI · 2019 to 2026
$125.4M
Systems BiologyU19AG023122 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI Thomas Girke, NICHOLAS Joseph SCHORK · 2004 to 2026
$102.6M
Identifying protective omics profiles in centenarians and translating these into preventive and therapeutic strategiesUH3AG064704 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI PERLS, THOMAS T, SEBASTIANI, PAOLA · 2022 to 2025
$14.7M
Integrative Omics to enhance therapeutics development for healthy agingUH3AG064706 · NIA · TRANSLATIONAL GENOMICS RESEARCH INST · PI MILLER, RICHARD A, SCHORK, NICHOLAS JOSEPH · 2021 to 2024
$3.3M
NIA NIH HHS U19 AG023122NIA NIH HHS U19 AG063893NIA NIH HHS UH3 AG064704NIA NIH HHS UH3 AG064706
6 · The paper itself

Abstract

Quantitative trait loci (QTL) denote regions of DNA whose variation is associated with variations in quantitative traits. QTL discovery is a powerful approach to understand how changes in molecular and clinical phenotypes may be related to DNA sequence changes. However, QTL discovery analysis encompasses multiple analytical steps and the processing of multiple input files, which can be laborious, error prone, and hard to reproduce if performed manually. In order to facilitate and automate large-scale QTL analysis, we developed the

Identifiers

PMID38370654
PMCPMC10874520
OpenAlexW4391340699

What OpenQuestion 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 OpenQuestion graph.