Download CGGA data
*It was updated on Jan 4, 2022, and older
versions is available here.
Open access to single cell sequencing data from the CGGA network
(6,148 cells from 73 regions of 13 glioma patients)
DataSet ID: scRNA-seq |
Data type: Single-cell sequencing |
Platform: STRT-seq |
Total 6,148 cells, involving in 73 regions from 13 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: WESeq_286 |
Data type: Whole-exome sequencing |
Platform: Agilent SureSelect kit v5.4 & Illumina HiSeq 4,000 |
Total number of samples: 286 |
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. Hu, H., Mu, Q., Bao, Z., et al. (2018). Mutational Landscape of Secondary Glioblastoma Guides MET-Targeted Trial in Brain Tumor. Cell 175, 1665-1678 e1618. 3. Jiang, T., Mao, Y., Ma, W., et al. (2016). CGCG clinical practice guidelines for the management of adult diffuse gliomas. Cancer Lett 375(2):263-273. |
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DataSet ID: mRNAseq_693 |
Data type: mRNA sequencing |
Platform: Illumina HiSeq |
Total number of samples: 693 |
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. Wang, Y., Qian, T., You, G., et al. (2015). Localizing seizure-susceptible brain regions associated with low-grade gliomas using voxel-based lesion-symptom mapping. NEURO-ONCOLOGY. 17(2): 282-288. 3. Liu, X., Li, Y., Qian, Z., et al. (2018). A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomas. NEUROIMAGE-CLINICAL. 20(1070-1077. |
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DataSet ID: mRNAseq_325 |
Data type: mRNA sequencing |
Platform: Illumina HiSeq 2000 or 2500 |
Total number of samples: 325 |
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. Bao, Z.S., Chen, H.M., Yang, M.Y., et al. (2014). RNA-seq of 272 gliomas revealed a novel, recurrent PTPRZ1-MET fusion transcript in secondary glioblastomas. Genome research 24, 1765-1773 3. Zhao, Z., Meng, F., Wang, W., et al. (2017). Comprehensive RNA-seq transcriptomic profiling in the malignant progression of gliomas. Scientific data 4, 170024 |
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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: 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