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• Hiseq 2000 and GA whole genome sequecing of 14 paired hepatocellular carcinomas

  Dataset EGAD00001001645

• AML exome sequencing

  Raw data (fastq files) from whole exome sequencing of AML patients (paired diagnosis and complete remission samples)

  Dataset EGAD00001002116

• COVID-19 Postmortem Medulla and Olfactory Mucosa snRNA-seq

  Time-dependent characterization of CNS response in COVID-19

  Dataset EGAD00001009075

• H3Africa TrypanoGEN+ Fastq

  TrypanoGEN+ data containing fastq files of 183 samples from DRC, Malawi and Uganda using NextSeq500.

  Dataset EGAD00001011666

• Sardinia Population SNPs frequencies

  List of SNPs, and their frequencies, extracted from a low pass whole genome sequencing of 3,514 individuals.

  Dataset EGAD00001003141

• Chordoma_Targeted_Sequencing_Study

  This Study uses a focused bespoke bait pull down library method to target findings of Chordoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Study EGAS00001000280

• Osteosarcoma_Targeted_Sequencing_Study

  This Study uses a focused bespoke bait pull down library method to target findings of Osteosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Study EGAS00001000278

• Meningioma_Targeted_Sequencing_Study

  This Study uses a focused bespoke bait pull down library method to target findings of Meningioma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these findings in a larger set of patient samples.

  Study EGAS00001000282

• Childhood Cancer Model Atlas

  we establish a single-site collection of 243 cell lines, including 207 paediatric cancer cell lines representing 14 distinct extracranial and brain childhood tumour types. We subjected 164 paediatric cancer cell lines to multi-omic analyses across three dimensions (DNA-sequencing, RNA-sequencing, DNA methylation) to classify them based on clinically relevant molecular subtypes.

  Study EGAS00001006320

• Epigenome cohort 30 Patient DNA and RNA

  This dataset includes RNA-seq, DNA and Chip-Seq data of samples from our paper.

  Dataset EGAD00001009041