Evidence map›Paper›PMID 36778366›Full record

ArticlebioRxiv : the preprint server for biology2023

Construction of a searchable database for gene expression changes in spinal cord injury experiments.

Eric C Rouchka, Carlos de Almeida, Randi B House, Jonah C Daneshmand, Julia H Chariker, Sujata Saraswat-Ohri, Cynthia Gomes, Morgan Sharp, Alice Shum-Siu, Greta M Cesarz and 2 more

Open access · greenAbstract readPreprint
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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 1 institution in 1 country.

Eric C RouchkaDepartment of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, University of Louisville, Louisville, KY USA.
Carlos de AlmeidaTranslational Neuroscience Program, School of Interdisciplinary and Graduate Studies, University of Louisville, Louisville, KY.
Randi B HouseKentucky Spinal Cord Injury Research Center, School of Medicine, University of Louisville, Louisville, KY.
Jonah C DaneshmandBioinformatics Program, School of Interdisciplinary and Graduate Studies, University of Louisville, Louisville, KY.
Julia H CharikerKentucky IDeA Networks of Biomedical Research Excellence (KY INBRE) Bioinformatics Core, University of Louisville School of Medicine, 522 East Gray Street, Louisville, KY USA 40202.
Sujata Saraswat-OhriKentucky Spinal Cord Injury Research Center, School of Medicine, University of Louisville, Louisville, KY.
Cynthia GomesKentucky Spinal Cord Injury Research Center, School of Medicine, University of Louisville, Louisville, KY.
Morgan SharpKentucky Spinal Cord Injury Research Center, School of Medicine, University of Louisville, Louisville, KY.
Alice Shum-SiuKentucky Spinal Cord Injury Research Center, School of Medicine, University of Louisville, Louisville, KY.
Greta M CesarzKentucky Spinal Cord Injury Research Center, School of Medicine, University of Louisville, Louisville, KY.
Jeffrey C PetruskaKentucky Spinal Cord Injury Research Center, School of Medicine, University of Louisville, Louisville, KY.
David S K MagnusonTranslational Neuroscience Program, School of Interdisciplinary and Graduate Studies, University of Louisville, Louisville, KY.
University of Louisville · US

Funding

WKU Lead Faculty AwardP20GM103436 · NIGMS · UNIVERSITY OF LOUISVILLE · PI ERIC C ROUCHKA · 2012 to 2026
$60.1M
NIGMS NIH HHS P20 GM103436
6 · The paper itself

Abstract

Spinal cord injury (SCI) is a debilitating disease resulting in an estimated 18,000 new cases in the United States on an annual basis. Significant behavioral research on animal models has led to a large amount of data, some of which has been catalogued in the Open Data Commons for Spinal Cord Injury (ODC-SCI). More recently, high throughput sequencing experiments have been utilized to understand molecular mechanisms associated with SCI, with nearly 6,000 samples from over 90 studies available in the Sequence Read Archive. However, to date, no resource is available for efficiently mining high throughput sequencing data from SCI experiments. Therefore, we have developed a protocol for processing RNA-Seq samples from high-throughput sequencing experiments related to SCI resulting in both raw and normalized data that can be efficiently mined for comparisons across studies as well as homologous discovery across species. We have processed 1,196 publicly available RNA-seq samples from 50 bulk RNA-Seq studies across nine different species, resulting in an SQLite database that can be used by the SCI research community for further discovery. We provide both the database as well as a web-based front-end that can be used to query the database for genes of interest, differential gene expression, genes with high variance, and gene set enrichments.

Indexed as

bulk RNA-Seqdifferential gene expressionODC-SCIRNA-SeqSCIspinal cord injurySQLitetranscriptomics

Identifiers

PMID36778366
PMCPMC9915599
OpenAlexW4319232439

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.