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• Exome sequencing reads

  Exome sequencing reads of two UFM individuals and their family members (totally 11 individuals) belonging to two different Fragile X families. Alignment files in BAM format are provided.

  Dataset EGAD00001002276

• subset of WGS data from umbrella study EGAS00001004338, used in EGAS00001004786

  linking 58 samples/58 runs of WGS from EGAS00001004338 Umbrella study to EGAS0001004786 study

  Dataset EGAD00001006614

• B Cell Receptor Study From Metastatic Breast Cancer Tumour Samples

  B and T cells are key components of the adaptive immune system and play an important role in anti-cancer immunity. In this study, we performed an integrative analysis of the B cell and T cell repertoires across 27 metastatic breast tumours obtained from 8 donors with therapy-resistant lethal metastatic breast cancer at the time of a warm autopsy.

  Study EGAS00001006976

• LCM_WGS__Thyroid_

  Whole genome sequencing through the low-input DNA pipeline in thyroid samples. Tissue will be processed either from laser capture microdissection or directly from bulk frozen/fixed/paraffin-embedded tissue. Insights will be gained here directly from the sequencing but also from using the data as a matched normal in Exome Nanoseq. Thyroid samples will be obtained from patients with and without thyroid disease.

  Study EGAS00001007913

• The G2 gene expression signature and MYC overexpression are independent poor prognostic factors in childhood high-grade osteosarcoma

  Key objective Are the prognostic transcriptomic G1/G2 gene expression signature, MYC overexpression, and MYC amplification replicable stratifying biomarkers for future clinical trials in high-grade osteosarcoma? Knowledge gathered In an unselected cohort, the G2 gene expression signature and MYC overexpression, but not MYC amplification, were independently associated with poor event-free and overall survival. Relevance Transcriptomic biomarkers may serve as stratifying factors that guide the management of patients with high-grade osteosarcoma. Current data underlines the importance of prospective validation of the G1/G2 signature and MYC overexpression in an international, multicenter, study.

  Dataset EGAD00001015503

• Multi-Omic Analysis of Von Willebrand Factor Regulation in Endothelial Colony Forming Cells

  This study evaluated the multi-omic analysis of endothelial cells with a focus on von Willebrand factor regulation, and investigated aspects of endothelial regulation in the context of blood disorders. The data available at dbGaP consist of multi-omic analyses of these cells. 

  Study phs002731

• DNA-seq BAM files from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by HPAH

  Paired-end DNA-seq BAM files from 16 carriers of the BMPR2 p.Arg491Gln mutation in a family affected by hereditary pulmonary arterial hypertension (HPAH). Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). FASTQ files were processed at the CNAG (Barcelona) using the GEM short-read aligner on the human genome version hs37d5, producing a total of 16 BAM files.

  Dataset EGAD00001005757

• RNA-Seq of GM adipose tissue samples

  This dataset contains 210 fastq files (RNA sequencing was performed in two centers) from 105 individuals (106 files in subcutaneous tissue and 104 files in visceral tissue). Of the 210 fastq files, 129 files are in PEx100 mode (appeared in a single fastq file) and 81 files are in PEx49bp mode (appeared in two separate fastq files). Sequencing was done on the Illumina HiSeq2000 platform.

  Dataset EGAD00001010253

• Concepción Aguilera belongs to the Department of Biochemistry and Molecular Biology II from the University of Granada and is head of the molecular biology research group BIONIT (CTS-461).

  Dac EGAC00001000779

• Genome and transcriptome sequence data from a metastatic cancer to the breast patient

  Genome and transcriptome sequence data from a metastatic cancer to the breast patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001010959