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• DAC for "Drug Development against Tumor Microtube Networks in Glioblastoma"

  This is the DAC for the study "Drug Development against Tumor Microtube Networks in Glioblastoma" of Dirk C. Hoffmann, Dirk.Hoffmann@dkfz.de and Frank Winkler, Frank.Winkler@med.uni-heidelberg.de

  Dac EGAC50000000326

• CRC and UC WES samples

  This is the dataset used to produce results for the report "NOUS-209 off-the-shelf immunotherapy has the potential to hit primary and metachronous colorectal and urothelial cancer in Lynch syndrome"

  Dac EGAC50000000782

• Haukeland University Hospital Data Access Committee for STRAT-PARK datasets archived in Federated EGA Norway

  This is the Data Access Committee mandated by Haukeland University Hospital for the STRAT-PARK cohort: an initiative to stratify Parkinson's disease.

  Dac EGAC50000000428

• MM GWAS dataset

  This is a meta-analysis of myeloma datasets, both with and without the UK Biobank cohort included.

  Dataset EGAD50000000422

• Leptomeningeal melanocytic tumour

  This is the first whole exome sequencing analysis of a primary meningeal melanocytic tumour (MMT) alongside the patients germline. Here we report the CRAM files from the tumour and germline.

  Dataset EGAD00001003750

• Transcriptomic profiling of human small intestine macrophage and DC subsets

  Using low input SMART-seq protocol, the whole transcriptome of human small intestine macrophage subtypes is characterized.

  Dataset EGAD00001003581

• PacBio data of de novo assembly individual EGYPT

  This is the PacBio long read data used for performing de novo assembly of the EGYPT individual (mapped against GRCh38).

  Dataset EGAD00001006034

• HEMOGLOBIN HAPLOTYPES IN ABIDJAN

  This is a prospective study with 100 participants. The enzymatic digestion profiles after conventional PCR allowed the identification of different haplotypes of hemoglobin in Abidjan.

  Dataset EGAD00001008546

• danMAC5

  Three whole genome sequecing of three independent cohorts. The three cohorts derives from projects including samples of inviduals with Danish origin. Data is deviden into males and female and compiled.

  Dataset EGAD00001009756

• Whole-Genome Sequencing in Multiplex Epilepsy Families

  Epilepsy is one of the most common neurologic disorders, affecting approximately 4% of individuals at some time in their lives. More than 30% of people with epilepsy continue to have seizures despite treatment, and improved approaches to treatment and prevention are sorely needed. In the search for new strategies to reduce the burden of disease, the discovery of specific genes that influence risk offers a novel opportunity to clarify pathogenic mechanisms, identify susceptible individuals prior to seizure onset, and treat and prevent seizures in people at risk. Despite clear evidence of the importance of genetics in susceptibility to epilepsy, only limited progress has been made in identifying the specific genes that influence risk. One of the greatest challenges for genetic research on this disorder is its extreme clinical and genetic heterogeneity. Although epilepsy is broadly defined by recurrent unprovoked seizures, it is so variable in its clinical manifestations, natural history, and treatment response that most epileptologists view it as a collection of different syndromes ("epilepsies") with distinct etiologies. The genetic effects on susceptibility are also likely to be extremely variable, ranging from rare variants with high penetrance (some of which produce Mendelian patterns of inheritance) to common variants with low penetrance. Recent findings strongly suggest that rare gene variants play a major role in the genetic architecture of the epilepsies. The purpose of this study was to discover new genetic risk factors for epilepsy. The primary approach was to use whole-genome sequencing to interrogate classes of genetic variants, including very rare variants, in multiplex families. Our main hypothesis was that, in at least some proportion of these families, a single variant would explain all instances of epilepsy. Variants identified within the families could then be tested for cosegregation within the family and also validated by seeing enrichment in sporadic epilepsy cases. Furthermore, understanding the impact of rare variation in epilepsy also has the potential to provide insight into the genetic architecture of other complex human diseases. Our analysis focused on families containing multiple individuals with non-acquired (idiopathic or unknown cause) epilepsy under the hypothesis that these would be enriched for genetic control. The families studied had been previously collected and phenotyped in detail, and contain an average of 3.8 individuals per family with a range of different types of epilepsy. We selected one or two affected individuals from each family for sequencing. This work has generated NGS data on 60 samples from 29 multiplex epilepsy families. We have established that, under a monogenic model of inheritance, sequencing pairs of distantly related relatives is an effective method for reducing the number of candidate variants. Critically, we have found that no single variant can explain a large proportion of these epilepsy families. This work emphasizes that identifying causal variants among the many genetic candidates found in this work will require very large sample sizes and gene-based analyses.

  Study phs000690