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Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients

Gliomas are the most common and malignant intracranial tumors in adults. Recent studies have revealed the significance of functional genomics for glioma pathophysiological studies and treatments. However, access to comprehensive genomic data and analytical platforms is often limited. Here, we develo...

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Detalles Bibliográficos
Autores principales: Zhao, Zheng, Zhang, Ke-Nan, Wang, Qiangwei, Li, Guanzhang, Zeng, Fan, Zhang, Ying, Wu, Fan, Chai, Ruichao, Wang, Zheng, Zhang, Chuanbao, Zhang, Wei, Bao, Zhaoshi, Jiang, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8498921/
https://www.ncbi.nlm.nih.gov/pubmed/33662628
http://dx.doi.org/10.1016/j.gpb.2020.10.005
Descripción
Sumario:Gliomas are the most common and malignant intracranial tumors in adults. Recent studies have revealed the significance of functional genomics for glioma pathophysiological studies and treatments. However, access to comprehensive genomic data and analytical platforms is often limited. Here, we developed the Chinese Glioma Genome Atlas (CGGA), a user-friendly data portal for the storage and interactive exploration of cross-omics data, including nearly 2000 primary and recurrent glioma samples from Chinese cohort. Currently, open access is provided to whole-exome sequencing data (286 samples), mRNA sequencing (1018 samples) and microarray data (301 samples), DNA methylation microarray data (159 samples), and microRNA microarray data (198 samples), and to detailed clinical information (age, gender, chemoradiotherapy status, WHO grade, histological type, critical molecular pathological information, and survival data). In addition, we have developed several tools for users to analyze the mutation profiles, mRNA/microRNA expression, and DNA methylation profiles, and to perform survival and gene correlation analyses of specific glioma subtypes. This database removes the barriers for researchers, providing rapid and convenient access to high‐quality functional genomic data resources for biological studies and clinical applications. CGGA is available at http://www.cgga.org.cn.