DAC
METABRIC data access committee
This DAC controls 10 datasets:
| Dataset ID | Description | Technology | Samples |
|---|---|---|---|
| EGAD00010000442 | Affymetrix SNP 6.0 CEL files | Affymetrix_SNP6_raw | 1302 |
| EGAD00010000436 | Illumina HT 12 IDAT files | Illumina HT 12 | 1302 |
| EGAD00010000268 | Metabric breast cancer samples (Expression raw data) | Illumina HT 12 | 543 |
| EGAD00010000266 | Metabric breast cancer samples (Genotype raw data) | Affymetrix SNP 6.0 | 543 |
| EGAD00010000270 | Metabric breast cancer samples (Images) | Aperio image - H&E stained tissue_section | 564 |
| EGAD00010000162 | Illumina HT 12 IDATS | Illumina HT 12 | 2136 |
| EGAD00010000164 | Affymetrix 6.0 CEL files | Affymetrix SNP 6.0 | 1992 |
| EGAD00010000158 | Affymetrix 6.0 cel files | Affymetrix SNP 6.0 | 1001 |
| EGAD00010000160 | Illumina HT 12 IDATS | Illumina HT 12 | 1001 |
| EGAD00001002115 | Targeted sequencing of 173 genes in 2433 primary breast tumours. Data includes 2433 tumour samples, 523 adjacent normal (breast) samples and 127 blood samples. Libraries were prepared with Illumina's Nextera custom enrichment kit targetting all the exons of the most frequently mutated breast cancer genes. Libraries were multiplexed (48 libraries per lane) and sequenced on Illumina HiSeq 2000 (100bp paired-end reads). Somatic mutations were calling with a custom pipeline. We identified 40 mutation-driver (Mut-driver) genes, and determined associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assessed the clonal states of Mut-driver mutations, and estimated levels of intra-tumour heterogeneity using mutant-allele fractions. The results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies. Referece: Pereira et al. (2016) The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nature Communications | 3083 |
