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• How are we funded?

  How are we funded? The EGA is provided infrastructure, administrative support, advisory input, and other relevant and necessary aspects by: CRG The EGA at the CRG is funded and supported by “La Caixa Foundation”, The Generalitat de Catalunya (Catalan Government), the Spanish Ministerio de Asuntos Económicos y Transformación Digital (Spanish Government) and the Instituto de Salud Carlos III. The Generalitat de Catalunya contributes with funding to the CRG and to the Barcelona Supercomputing Centre (BSC). The Barcelona Supercomputing Center is decisively contributing to EGA by providing the required compute, storage and networking resources, as well as key personnel for shared operations of EGA infrastructure. EMBL-EBI As part of the European Molecular Biology Laboratory (EMBL), the EGA at EMBL’s European Bioinformatics Institute receives funding from the governments of EMBL’s member states. The UK government, via UK Research and Innovation, also continues to support EMBL-EBI technical infrastructure, with EMBL supporting operational costs. A major source of funding for the EGA both at CRG and EMBL-EBI are competitive projects.The EGA resource continues to be funded through strategic engagement in collaborative partnerships and projects. Please see our projects page for more information. Other funders include the European Commission, the US National Institutes of Health, the Wellcome Trust, UK Research Councils, and our Industry Programme partners. Last updated on October, 2024.

  Documentation about/projects-and-funders/funders

• Patient-derived conditionally reprogrammed cells (CRCs) were established and characterized to assess their biological properties and to apply these to test the efficacies of drugs.

  RNA seq data was used for the characterization and profiling of the created patient-derived cells and in vivo tissue.

  Study EGAS00001001702

• WES data generated in multifocal ileal NETs study

  This dataset includes whole-exome sequencing data for multifocal ileal tumor samples from two patients. Exonic sequences were enriched using the Agilent V2 capture probe set and sequenced by 76-bp paired-end reads using the Illumina Genome Analyzer IIx system with a mean coverage of 80x for each base

  Dataset EGAD00001006408

• WES fastq files of IPDGC UK cohort

  As part of the International Parkinson's Disease Genomics Consortium, exomes of Parkinson's disease (PD) patients and healthy controls were sequenced to study the genetic etiology of PD. This UK cohort consists of 70 PD patients. Researchers can apply for access to fastq files for this cohort.

  Dataset EGAD00001003096

• Mapping of runs back to samples for snRNASeq data

  Mapping of runs back to samples for PDN, PDO and TIS snRNASeq data. 4 sets of matched PDN, PDO and TIS samples (12 unique samples total) underwent pooled snRNASeq (Parse Biosciences). 2 sublibraries were created from this and sequenced at separate times

  Dataset EGAD00001015609

• RNA-sequencing data from 195 B-cell precursor acute lymphoblastic leukemias and mate pair whole genome sequencing data from 15 B-cell precursor acute lymphoblastic leukemias

  Fusion genes are potent driver mutations in cancer. In this study, we delineate the fusion gene landscape in a consecutive series of 195 pediatric B-cell precursor acute lymphoblastic leukemia (BCP ALL). Using RNA-sequencing, we find in-frame fusion genes in 127 (65%) cases, including 27 novel fusions. We describe a new subtype characterized by recurrent IGH-DUX4 or ERG-DUX4 fusions, representing 4% of cases, leading to overexpression of DUX4 and frequently co-occurring with intragenic ERG deletions. Furthermore, we identify a subtype characterized by an ETV6-RUNX1-like gene expression profile and coexisting ETV6 and IKZF1 alterations. Taken together, this study provides a detailed overview of fusion genes in pediatric BCP ALL and adds new pathogenetic insights, which may improve risk stratification and provide novel therapeutic options in this disease.

  Study EGAS00001001795

• Predicting brain tumor recurrence: development and validation of a DNA-methylation based nomogram in meningioma

  Our work is the first to demonstrate the transformative utility of integrating clinical and molecular factors for use beyond simple classification into the realm of individualized prognostication for any brain tumor. Using our developed and validated tools that are publicly available, clinicians will be able combine clinical and molecular factors to determine an individualized probability of recurrence for patients with meningiomas. This represents a major advance in the field of personalized medicine for neuro-oncology, and the use of this tool can help clinicians overcome one of the most challenging limitations we face when treating patients with meningiomas.

  Study EGAS00001003490

• The CCA Genome Core is responsible for archiving the sequencing data generated by the Cancer Centre Amsterdam (CCA).

  Dac EGAC00001000181

• Psoriasis PBMCs

  This DAC is for the purpose of controlling access to Psoriasis PBMC scRNA-seq data of the study Spermidine/spermine N1-acetyltransferase controls tissue-specific regulatory T cell function in chronic inflammation

  Dac EGAC50000000470

• COMET TCRseq raw data

  This is the raw TCRseq data for the manuscript T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases.

  Dataset EGAD00001010269