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...

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Detalles Bibliográficos
Autores principales: Liu, Candace C., Guo, Yongjian, Vrindten, Kiera L., Lau, William W., Sparks, Rachel, Tsang, John S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307621/
https://www.ncbi.nlm.nih.gov/pubmed/35880119
http://dx.doi.org/10.1016/j.xpro.2022.101474
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author Liu, Candace C.
Guo, Yongjian
Vrindten, Kiera L.
Lau, William W.
Sparks, Rachel
Tsang, John S.
author_facet Liu, Candace C.
Guo, Yongjian
Vrindten, Kiera L.
Lau, William W.
Sparks, Rachel
Tsang, John S.
author_sort Liu, Candace C.
collection PubMed
description 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).
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spelling pubmed-93076212022-07-24 OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data Liu, Candace C. Guo, Yongjian Vrindten, Kiera L. Lau, William W. Sparks, Rachel Tsang, John S. STAR Protoc Protocol 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). Elsevier 2022-07-20 /pmc/articles/PMC9307621/ /pubmed/35880119 http://dx.doi.org/10.1016/j.xpro.2022.101474 Text en © 2022. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Liu, Candace C.
Guo, Yongjian
Vrindten, Kiera L.
Lau, William W.
Sparks, Rachel
Tsang, John S.
OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data
title OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data
title_full OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data
title_fullStr OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data
title_full_unstemmed OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data
title_short OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data
title_sort omicc: an expanded and enhanced platform for meta-analysis of public gene expression data
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307621/
https://www.ncbi.nlm.nih.gov/pubmed/35880119
http://dx.doi.org/10.1016/j.xpro.2022.101474
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