METABRIC data access committee

Dac ID Contact Person Email Access Information
EGAC00001000484 Marion Karniely metabric [at] cruk [dot] cam [dot] ac [dot] uk

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