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• Genome-wide genotyping data and exome sequencing of 100 European-descent and 100 African-descent Belgians used in the EGAS00001001895 study

  We recruited 100 healthy, male donors of self-reported European descent (EUB) and 100 of self-reported African descent (AFB) (Ghent, Belgium). For each participant, peripheral blood mononuclear cells (PBMCs) were isolated from whole blood on Ficoll-Paque density gradients. Monocytes were then positively selected with magnetic CD14 microbeads and exposed for 6 hours to different ligands activating TLR4 (LPS), TLR1/2 (Pam3CSK4), TLR7/8 (R848) and to a human seasonal influenza A virus (IAV). High-quality RNA was obtained from unstimulated and stimulated monocytes for 970 of the 1000 samples (200 x 5 conditions), and was sequenced on an Illumina HiSeq2000. On average, 34 million 101-bp single-end reads were obtained per sample.

  Dataset EGAD00001002714

• NGS data of human NES cells and tumors

  Raw RNA-seq data for WT and 2 Gorlin NES cells, tumors derived from MYCN mis-expressed WT NES cells, tumors derived from Gorlin NES cells, and tumors derived from Gorlin NES cells transduced with mutant DDX3X (R351W and R534S) and CRISPR/Cas9 targeting GSE1 (each sample has 3 replicates/tumors except Gorlin NES cell tumors have 4). Raw whole exome sequencing data for WT and Gorlin 1 NES cells, tumors derived from MYCN mis-expressed WT NES cells, and tumors derived from Gorlin NES cells (each sample has 3 replicates/tumors except Gorlin NES cell tumors have 4). Raw data for amplicon sequencing of GSE1 and KDM3B at regions targeted by CRISPR/Cas9 in Gorlin NES cells.

  Dataset EGAD00001004990

• Evaluation of protocols for rRNA depletion-based RNA sequencing of nanogram inputs of mammalian total RNA

  Next generation RNA-Sequencing (RNA-seq) is a flexible approach that can be applied to e.g. global quantification of transcript expression, the characterization of RNA structure such as splicing patterns and profiling of expressed mutations. Many RNA-seq protocols require up to microgram levels of total RNA input amounts to generate high quality data, and thus remain impractical for the limited starting material amounts typically obtained from rare cell populations, such as those from early developmental stages or from laser micro-dissected clinical samples. Here, we present an assessment of the contemporary ribosomal RNA depletion-based protocols, and identify those that are suitable for inputs as low as 1-10 ng of intact total RNA and 100-500 ng of partially degraded RNA from formalin-fixed paraffin-embedded tissues.

  Dataset EGAD00001005316

• Variant calls for "Quality of Whole Genome Sequencing from Blood versus Saliva Derived DNA in Cardiac Patients"

  Paired blood and saliva samples from five unrelated individuals were directly compared for quality of whole genome sequencing. Two (Sample Pairs 1 and 2) were female probands diagnosed with tetralogy of Fallot, a type of congenital heart disease, and three (Sample Pairs 3, 4 and 5) were male probands diagnosed with hypertrophic cardiomyopathy. WGS was performed using Illumina HiSeq X to a target average coverage depth of 30x and a read length of 150 bp. The resulting reads were not filtered for minimum quality in order to avoid losing possible contaminant reads. Sequencing read alignment was done using Isaac Aligner to human genome build hg19. Short variant i.e. single-nucleotide variant (SNV) and small insertion-deletion (indel) calling was performed using Isaac Variant Caller with default parameters.

  Dataset EGAD00001005772

• Deep targeted DNA sequencing dataset for the study "Molecular characteristics in Burkitt lymphoma over age groups"

  We performed deep targeted DNA sequencing with a panel of 134 selected cancer-related genes previously identified to be recurrently mutated in BL/B-AL. A Nextera rapid capture custom kit was designed using the Illumina DesignStudio. For every gene, all regions in which previous mutations had been described were covered. For 40 of these genes, the entire coding sequence was covered. Targeted deep sequencing was performed on a MiSeq-Sequencer using MiSeq Reagent Kit v2 (300 cycle) with 24 samples per run. There are 396 samples in this targetedDNAseq-dataset with 298 tumors (288 patients and 10 cell lines) and 98 normals. There are 132 female, 262 male, and 2 unknown gender samples in this dataset.

  Dataset EGAD00001007708

• Fastq files for the single cell RNAseq data of Follicular lymphoma study

  Fastq files for the single cell RNAseq data of Follicular lymphoma study. This dataset includes the paired single cell RNA sequencing data for 23 samples.

  Dataset EGAD00001008595

• Bulk-tissue RNA-sequencing paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control individuals ( anterior prefrontal cortex & cerebellar cortex – 4 individuals, putamen- 3 individuals)

  Profiling of paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen samples by bulk-tissue RNA-sequencing. Samples were derived from 4 post-mortem neuropathologically-confirmed control individuals ( anterior prefrontal cortex – 4 individuals, cerebellar cortex – 4 individuals, putamen- 3 individuals). Paired-end FASTQ files for each of the human samples are provided. Fastp (v 0.20.0), a fast all-in-one FASTQ pre-processor, was used for adapter trimming, read filtering and base correction. Fastp default settings were used for quality filtering and base correction. Further details on parameters used are available here: https://github.com/RHReynolds/RNAseqProcessing .

  Dataset EGAD00001009264

• Associate Vice President for Research Administration & Director

  Dac EGAC00001003114

• DAC for Duke-NUS genomic sequencing projects

  Dac EGAC00001000256

• DAC for Whole Genome Sequencing of ASD quartet families

  Dac EGAC00001000288

• The Shlien Lab, The Hospital for Sick Children

  Dac EGAC00001000289

• DAC for IGMM / Usher Institute, University of Edinburgh

  Dac EGAC00001000365

• DAC for esophageal squamous cell carcinoma genomic data

  Dac EGAC00001000444

• MacFeeters Hamilton Centre for Neuro-Oncology Research (MHC-NOR)

  Dac EGAC00001000510

• DAC for Dave Lab, Duke University

  Dac EGAC00001000538

• DAC for Single Cell Transcriptomics of Colorectal Cancer

  Dac EGAC00001000550

• Data access committee for BAMS exome sequencing data.

  Dac EGAC00001000583

• DAC for DCM-cases (149 human DCM samples)

  Dac EGAC00001000673

• DAC for DCM-controls (113 human non-DCM samples)

  Dac EGAC00001000674

• DAC for AA HCC patient from National Taiwan University

  Dac EGAC00001000708

• Institut Jules Bordet Data Access Committee for EGAS00001002685 study

  Dac EGAC00001000748

• Data Access Committee for Tumor Progression Study at Karolinska Institute

  Dac EGAC00001000778

• DAC for Institute of Human Genetics, Bonn, AGA Project

  Dac EGAC00001000831

• DAC for study Hypothalamic transcriptome in Prader-Willi syndrome

  Dac EGAC00001000869

• DAC for Genomic landscpae of Chordoid Glioma study

  Dac EGAC00001000906