Download CGGA data
*It was updated on Jan 4, 2023, and older
versions is available here.
Open access to read counts data
for RNA-seq of non-glioma controls
DataSet ID: scRNA-seq |
Data type: Single-cell sequencing |
Platform: STRT-seq |
Total 6,148 cells, involving in 73 regions from 14 patients. |
If you use this part of the data (or method
included in it), please consider to cite: 1. Li, GZ., Li, Lin., Li, YM., et al. An MRI radiomics approach to predict survival and tumour-infiltrating macrophages in glioma (2021). Brain 2022 Feb 6. 2. Zhao, Z., Zhang, KN., Wang, QW., et al. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients (2021). Genomics, Proteomics & Bioinformatics 19(1):1-12. 3. Yu, Kai., Hu, Yuqiong., Wu, Fan., et al. Surveying brain tumor heterogeneity by single-cell RNA-sequencing of multi-sector biopsies (2020). National Science Review 7(8):1306–1318 |
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DataSet ID: Spatiotemporal transcriptome data |
Data type: mRNA sequencing |
Platform: Illumina HiSeq |
Total number of samples: Longitudinal samples: 141; Spatial samples: 67 |
If you use this part of the data (or method
included in it), please consider to cite: 1. Zhao, Z., Zhang, KN., Wang, QW., et al. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients (2021). Genomics, Proteomics & Bioinformatics 19(1):1-12. 2. Feng, J., Zhao, Z., Wei, Y., Bao, Z., et al. Temporal and Spatial Stability of the EM/PM Molecular Subtypes in Adult Diffuse Glioma. (To be submitted). |
Further information and requests for resources should be directed to the Lead Contact, Tao Jiang or Xiaolong Fan (taojiang1964@163.com or xfan@bnu.edu.cn) |
DataSet ID: Image-genomic data |
Data type: Image-genomic data |
Platform: MRI |
Total number of samples: 274 |
If you use this part of the data (or method
included in it), please consider to cite: 1. Zhao, Z., Zhang, KN., Wang, QW., et al. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients (2021). Genomics, Proteomics & Bioinformatics 19(1):1-12. 2. Li, Y., Liang, Y., Sun, Z., et al. Radiogenomic analysis of PTEN mutation in glioblastoma using preoperative multi-parametric magnetic resonance imaging. Neuroradiology. 2019 Nov;61(11):1229-1237. |
Further information and requests for resources should be directed to the Lead Contact, Tao Jiang (taojiang1964@163.com) |
DataSet ID: methyl_159 |
Data type: DNA methylation microarray |
Platform: Illumina Infinium HumanMethylation27 Bead-Chips |
Total number of samples: 159 |
If you use this part of the data (or method
included in it), please consider to cite: 1. Zhao, Z., Zhang, KN., Wang, QW., et al. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients (2021). Genomics, Proteomics & Bioinformatics 19(1):1-12. |
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DataSet ID: microRNA_198 |
Data type: microRNA microarray |
Platform: human v2.0 miRNA Expression BeadChip (Illumina) |
Total number of samples: 198 |
If you use this part of the data (or method
included in it), please consider to cite: 1. Zhao, Z., Zhang, KN., Wang, QW., et al. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients (2021). Genomics, Proteomics & Bioinformatics 19(1):1-12. |
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DataSet ID: mRNA sequencing (non-glioma as control) |
Data type: mRNA sequencing |
Platform: Illumina HiSeq |
Total number of samples: 20 |
If you use this part of the data (or method
included in it), please consider to cite: 1. Zhao, Z., Zhang, KN., Wang, QW., et al. Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma Patients (2021). Genomics, Proteomics & Bioinformatics 19(1):1-12. |
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*Browse the 'About' section for details of
data processing