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• PCa mtDNA data

  50 paired benign/cancer samples from prostate tissue generated in 2 different runs - on 3 plates on the IonTorrent Proton. Total of 200 fastq.gz single end runs. Read length ~300 bp. %GC 44 Sequences per file approx 1 Mio.

  Dataset EGAD00001005945

• Profiling Chromatin Accessibility in Humans Using Adenine Methylation and Long-Read Sequencing

  This dataset includes raw nanopore, base-called, and 6mA frequency data for EcoGII-treated NA12878 and MCF7 chromatin samples. It also includes raw nanopore data for the HG002 EcoGII-treated DNA.

  Dataset EGAD00001015374

• RNA-Seq files for SJHGG study

  RNA-Seq files accompanying the paper titled "Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas".

  Dataset EGAD00001003905

• Exome sequencing of patients with acute promyelocytic leukemia

  The dataset consists in 64 fastq files from 23 patients with acute promyelocytic leukemia. Exome sequencing was conducted on several stages (Diagnosis, Remission, Relapse) for each patient. For 5 patients, only Diagnosis and Relapse samples are available.

  Dataset EGAD00001004043

• Whole Exome Data of RFWD3 Fanconi anemia patient

  Dataset contains one sample derived from gDNA of human fibroblasts. Files are in FASTQ format and were generated using the Agilent SureSelect Human All Exon 50Mb Kit and followed by Next Generation Sequencing on a HighSeq2000 instrument (Illumina).

  Dataset EGAD00001003311

• SLC9A3R1 variant associated with age-related hearing loss

  The dataset contains one BAM file that includes a SLC9A3R1 variant identified in two Italian patients affected by age-related hearing loss. Data have been produced by targeted re-sequencing, using Ion Torrent PGM platform.

  Dataset EGAD00001004171

• Liverpool Preterm Birth Biomarker Study

  Preterm birth is a multifactorial condition defined as birth less than 37 weeks of gestation. This study aimed to identify early pregnancy biomarkers from maternal genome-wide and transcriptome-wide data of women experiencing two types of spontaneous PTB (sPTB): spontaneous preterm birth (SPTB) and preterm premature rupture of membranes (PPROM). Whole blood samples were obtained from women with singleton pregnancies (N=567) recruited at the Liverpool Women’s Hospital at 16 and 20 weeks of gestation. Women with a previous history of sPTB pregnancies <34 weeks were categorised on their index pregnancy outcome as spontaneous preterm birth (SPTB) and preterm premature rupture of membranes (PPROM) or high-risk term control (HTERM, ≥37 weeks). Women with no history of SPTB/PPROM and delivered at term were LTERM (≥39 weeks of gestation). DNA was genotyped on the UK Biobank Axiom™ array (Applied Biosystems™, Thermo Fisher Scientific) and RNA who processed using the Clariom™ D Human assay (Thermo Fisher Scientific). Genome-wide association analysis, differential expression analysis and expression quantitative trait loci (eQTL) were completed.

  Study EGAS00001005076

• Genomic Landscape of High-Grade Neuroendocrine Neoplasms

  This project is a multi-omics study of high grade (grade 3) neuroendocrine neoplasms across diverse organs. Genomic analysis using low-pass whole genome sequencing for copy number analysis, whole exome sequencing and whole transcriptomic sequencing using RNAseq were performed. As high grade neuroendocrine neoplasms are highly lethal with a median survival of approximately 7 months, new insights are urgently needed for better prognosis, diagnosis and management. This study focuses on gene and pathway discoveries in this cancer, and includes samples from a diverse set of organs, including the lungs, gastroenteropancreatic tract, breast, prostate, head and neck and bladder. This study was made possible by a generous donation from The Helen B. Rodde Fund.

  Study phs002070

• Genomic Analysis of Diffuse Large B Cell Lymphoma

  Tumors from 383 newly diagnosed diffuse large B cell lymphoma were included in this study. Tumor DNA was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections, germline DNA was extracted from blood, and whole exome sequencing (WES) of all samples (n=340 tumor normal pairs) was performed using the Agilent SureSelect XT AllExon v5 + UTR kit and sequencing was carried out on an Illumina NovaSeq, 100 x 2 paired end reads. Tumor RNA (n=321) was extracted from formalin-fixed, paraffin embedded (FFPE) tissue sections and RNA sequencing was performed using the Illumina TruSeq RNA Exome Kit (Illumina) for library preparation, sequencing platform HiSeq 4000, 100 x 2 paired end reads.

  Study phs003634

• Swarm Learning to identify COVID-19, tuberculosis and leukemia patients based on blood transcriptomes

  Identification of patients with life-threatening diseases including leukemias or infections such as tuberculosis or COVID-19 is an important goal of modern precision medicine. However, there is an increasing divide between what is technically possible and what is allowed because of privacy legislation. We have recently illustrated that classical machine learning can identify leukemia patients based on their blood transcriptomes. To facilitate integration of any omics data from any data owner world-wide without violating privacy laws, we here introduce Swarm Learning (SL), a decentralized machine learning approach uniting edge computing, artificial intelligence (AI), blockchain and privacy protection without the need for a central coordinator thereby going beyond federated learning. To illustrate its feasibility, using more than 12,000 transcriptomes from peripheral blood mononuclear cells and more than 2,000 peripheral blood transcriptomes we demonstrate that SL of omics data distributed across different individual sites leads to disease classifiers that outperform those developed at individual sites. Yet, SL completely protects local privacy regulations by design. We propose this approach to noticeably accelerate the introduction of precision medicine.

  Dataset EGAD00001006231