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• Data Access Committee of CiRA Foundation

  The iPS Cell Stock Project promoted by the CiRA Foundation is intended to generate and distribute iPS cells for medical use so they can be effectively utilized for research and development of cell transplantation therapy and contribute to the advancement of regenerative medicine that may become a novel treatment for patients suffering from intractable diseases or trauma who are not expected to improve with conventional therapies. In order to achieve this objective, CiRA Foundation establish the DAC based on the basic policies and rules for handling analysis information including iPS cell stocks for the purpose of proper sharing of samples and analyzed data collected directly or indirectly from the donors of iPS cell stocks.

  Dac EGAC50000000128

• Molecular biomarkers for stratification periheral T cell lymphoma

  Peripheral T cell lymphoma (PTCL) is a diverse group of rare lymphoid malignancies with overall poor prognosis. Diverse biological mchanisms behind these diverse disease groups make targeted treatment challenging. Based on molecular biomarkers, more , the aim is to characterise more specific features for the different clinically defined PTCL for new future prognostic therapies.

  Study EGAS00001006691

• VESPA: Vanderbilt Electronic Systems for Pharmacogenomic Assessment

  The Vanderbilt Electronic Systems for Pharmacogenomic Assessment (VESPA) Project is a large electronic medical record (EMR)- and biobank-based initiative for translational pharmacogenomics discoveries. Key research resources utilized in this effort include the BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using EHR-derived structured and unstructured ("free text") data. Cohorts include subjects with primarily drug-response phenotypes, and most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Advanced informatics methods, such as natural language processing, were also used for some phenotypes. Algorithms used event-sequence analyses to establish temporal relationships between drugs and phenotypes. Both cases and control algorithms excluded records that contained specific comorbidities and were refined to achieve positive predictive value (PPV) > 90%. For automated algorithms failing to meet this threshold, manual review was coupled with algorithms to validate that the included cases were true positives. A total of 11,639 subjects met phenotyping criteria for a least one of the 28 phenotypes investigated. Across all phenotypes cases and controls, 90% were reused as either a case or control for a least one other phenotype. Data are deposited for individual phenotypes in the VESPA substudies. Substudies: VESPA: Genome Wide Association Study of Serum Creatinine during Vancomycin Therapy and Vancomycin Pharmacokinetics - phs000894 VESPA: Genome Wide Study of Clinically Diagnosed Ace Inhibitor Cough - phs000992

  Study phs000991

• DAC for DKFZ Recording physiological history of cells with chemical labeling

  DAC for the data in the publication "Recording physiological history of cells with chemical labeling" from DKFZ for Tobias Kessler (t.kessler@dkfz-heidelberg.de), Frank Winkler (frank.winkler@med.uni-heidelberg.de) and Kai Johnsson (johnsson@mr.mpg.de)

  Dac EGAC50000000054

• Targeted capture sequencing for LySeqST

  Targeted capture sequencing of 445 lymphoma samples and 13 normal samples for LySeqST: A targeted sequencing assay for robust genomic classification of diffuse large B-cell lymphoma.

  Dataset EGAD50000002290

• Exome sequencing data for LMS tumor and control samples

  The data set contains paired end fastq files for whole exome sequencing data for Leiomyosarcoma tumor and control samples

  Dataset EGAD00001003829

• Patient-Parent trio sequencing for 100 sporadic ID patients

  Single end short-read (50 bp) SOLiD 4 sequencing data for 300 individuals, constituting 100 patient-parent trios. For more details please read; http://www.nejm.org/doi/full/10.1056/NEJMoa1206524

  Dataset EGAD00001000680

• Mantle cell lymphoma exomes and genomes for finding driver mutations

  Tumor and normal exomes for 51 MCL patients and tumor and normal genomes for 34 MCL patients.

  Dataset EGAD00001006159

• DAC for Melanoma Exome Dataset for Identification of Mutated Epitopes

  Dac EGAC00001000546

• Helmholtz Centre for Infection Research, Centre for Individualised Medicine

  Dac EGAC00001002208