OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data
OMiCC (OMics Compendia Commons) is a biologist-friendly web platform that facilitates data reuse and integration. Users can search over 40,000 publicly available gene expression studies, annotate and curate samples, and perform meta-analysis. Since the initial publication, we have incorporated RNA-s...
Gespeichert in:
Veröffentlicht in: | STAR protocols 2022-09, Vol.3 (3), p.101474-101474, Article 101474 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | OMiCC (OMics Compendia Commons) is a biologist-friendly web platform that facilitates data reuse and integration. Users can search over 40,000 publicly available gene expression studies, annotate and curate samples, and perform meta-analysis. Since the initial publication, we have incorporated RNA-seq datasets, compendia sharing, RESTful API support, and an additional meta-analysis method based on random effects. Here, we provide a step-by-step guide for using OMiCC.
For complete details on the use and execution of this protocol, please refer to Shah et al. (2016).
[Display omitted]
•OMiCC (OMics Compendia Commons) is a free web-based tool for gene expression data reuse•Search publicly available studies to perform sample group comparisons to explore a disease•In meta-analysis, multiple studies are combined to identify coherent signals•OMiCC supports crowd-sharing and users can share their own analyses with the community
Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.
OMiCC (OMics Compendia Commons) is a biologist-friendly web platform that facilitates data reuse and integration. Users can search over 40,000 publicly available gene expression studies, annotate and curate samples, and perform meta-analysis. Since the initial publication, we have incorporated RNA-seq datasets, compendia sharing, RESTful API support, and an additional meta-analysis method based on random effects. Here, we provide a step-by-step guide for using OMiCC. |
---|---|
ISSN: | 2666-1667 2666-1667 |
DOI: | 10.1016/j.xpro.2022.101474 |