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Overview

Welcome to the CGGA - Chinese Glioma Genome Atlas! The CGGA database contains clinical and sequencing data of over 2,000 brain tumor samples from Chinese cohorts, and is equiped with a user-friendly web application for data storage and exploration. Currently, the CGGA includes image-genomic data (274), scRNA-seq data (6,148 cells, 73 regions from 14 patients), whole-exome sequencing data (286), mRNA sequencing data (693, batch 2), mRNA sequencing data (325, batch 1), mRNA microarray data (301), DNA methylation data (159), microRNA microarray data (198), mRNA seqencing data (20, non-glioma), and matched clinical data. In addition, we provide some tools to analyse DNA mutation profile, mRNA expression profile, methylation profile, and microRNA expression profile. Some utilities have been developed to allow users to analyze their own data. We hope that the CGGA database will remove barriers for researchers and provide fast and easy access to high quality functional genomic data resources for biological research and clinical applications.


Citation: Zhao Z, Zhang KN, Wang Q, et al. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients. Genomics, Proteomics & Bioinformatics. 2021 Feb;19(1):1-12. doi:10.1016/j.gpb.2020.10.005

News

Statistics

Dataset Data Type Sample Number Clinical Data Analyse
#total #pLGG #rLGG #pGBM #rGBM #sGBM histology grade age gender therapy survival
NewscRNA-seq STRT-seq 14 total 6,148 cells, involving in 73 surgically obtained biopsies from 14 patients. under construction
Image-genomic data MRI 274 274 glioma patients were collected retrospectively. under construction
WEseq_286 WESeq 286 126 58 54 48 0
mRNAseq_693
(batch 1)
RNA-seq 693 282 161 140 109 0
mRNAseq_325
(batch 2)
RNA-seq 325 144 38 85 24 30
mRNA-array_301 Microarray 301 156 18 108 5 11
methyl_159 Microarray 159 100 8 33 4 6
microRNA-array_198 Microarray 198 99 8 81 4 6

Features

Analyse the WEseq data

Analyse the mRNA data

Analyse the methylation data

Analyse the microRNA data

Download CGGA data

Questions or comments

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