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• Processed RNAseq data

  This dataset contains log2(TPM + 1) transformed counts for the 823 tumor samples profiled by RNAseq.

  Dataset EGAD00001006618

• Raw FASTq files

  This dataset contains FASTq files for tumors from the 823 patients profiled by RNAseq.

  Dataset EGAD00001006619

• Amplicon–Based Metagenomic Analysis.

  Amplicon-based fungal metagenomic sequencing for the identification of fungal species in brain tissue from Alzheimer's disease. The study consists in 14 samples, sequenced using Illumina's paired-end technology.

  Dataset EGAD00001003196

• Genome - MBD4-deficient AML

  Genome sequencing at diagnosis and post induction for WEHI-AML-1 and WEHI-AML-2. Whole genome sequencing was performed on an Illumina HiSeq X Ten.

  Dataset EGAD00001003568

• BGI study for primary and metastatic Chinese lung adenocarcinomas

  We sequenced 292 patients who were suffering NSCLC with Whole genome sequencing or Exome sequencing method.

  Dataset EGAD00001001397

• SCNA-Seq of tumor DNA samples

  Low coverage whole genome sequencing for the identification of somatic copy number alterations (SCNA) and focal amplification mapping of corresponding tumor material

  Dataset EGAD00001002150

• RNAseq for brainstem glioma

  RNAseq on Illumina HiSeq X Ten of brainstem glioma primary tumor sample

  Dataset EGAD00001006094

• 1_fibroblasts_HD_vs_Ctrl_DMSO_Branaplam

  n=4 Ctrl and n=4 HD fibroblasts lines were treated with DMSO or 10nM Branaplam for 72h and RNA-seq was performed.

  Dataset EGAD00001008807

• Paired-end RNA-seq analysis of the TERT promoter mutant GBM cell lines

  This dataset contains 9 RNA-seq BAM files. RNA was derived from TERT promoter mutant GBM cell lines and sequenced on an Illumina HiSeq4000 sequencer with paired-end reads and an average read length of 50 base pairs. Reads were aligned with TopHat (v2.0.14) using a GENCODE V19 transcriptome-guided alignment.

  Dataset EGAD00001005435

• Pediatric CNS tumor classification by DNA-methylation dataset

  In this study nanopore sequencing was applied to obtain sparse DNA methylation profiles from pediatric CNS tumor samples. A neural network was used to classify the tumor based on the obtained methylation profile.

  Dataset EGAD00010002599