henhaobio
Sign in

Journal of NeurotraumaBioinformaticsPeer-reviewed journal article

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

Eric Christian RouchkaiD, Carlos de AlmeidaiD, Randi B. House, Jonah C. DaneshmandiD, Julia H. CharikeriD, Sujata Saraswat-Ohri, Cynthia GomesiD, Morgan J. ForstoniD, Alice Shum-Siu, Greta M. Cesarz, Jeffrey C. PetruskaiD, David S.K. MagnusoniD

PDFDOIPreprint

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.

Citations
2
FWCI
0.40
Field percentile
top 39%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISStöckel '15Grillo-Risc '24Kyritsis '20Garcia '18Yasko '19Ruiz-Amezcu '24
59% semantic matchBioinformatics
Andreas Stöckel, Benjamin Paassen, Raphael Dickfelder+6 more·bioRxiv·Jan 12, 2015