Search Results - EGA European Genome-Phenome Archive

Multiple_Malignancy_Familial_Comparison

Patient (who has had multiple malignancies) has previously been found to harbour a pathogenic p53 variant which is probably mosaic. This finding is based on exome sequencing performed elsewhere. In this study we will resequence the locus in question to ascertain whether the variant is indeed mosaic.

Study EGAS00001000333

Single cell analysis reveals new evolutionary complexity in uveal melanoma

Uveal melanoma (UM) is a rare eye cancer that is highly aggressive and leads to metastatic death in up to half of patients. Here, we conduct droplet-based single-cell RNA sequencing of 59,915 neoplastic and non-neoplastic cells from 8 primary and 3 metastatic UMs. Single-cell VDJ sequencing of RNA is conducted to determine clonally expanded B/T- cell populations. Single-cell DNA sequencing of 1 primary and 1 metastasis is utilized.

Study phs001861

EXCEED Study

EXCEED is a longitudinal population-based cohort which facilitates investigation of genetic, environmental and lifestyle-related determinants of a broad range of diseases and of multiple morbidity through data collected at baseline and via electronic healthcare record linkage. Recruitment has taken place in Leicester, Leicestershire and Rutland since 2013 and is ongoing, with approximately 10,000 participants aged 30-69 to date. The population of Leicester is diverse and additional recruitment from the local South Asian community is ongoing.

Study EGAS00001003499

Synthetic - GDI synthetic data

Synthetic - The Genomic Data Infrastructure (GDI) project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure the GDI project (funding: EC H2020 under grant agreement number 101081813) is acknowledged.

Study EGAS50000000678

Pathogenesis and Immunity in Endemic Burkitt Lymphoma

This genomic landscape of Burkitt lymphoma represents a multimodal sequencing of tumors and control tissues and individuals to better understand the etiology, and molecular pathogenesis of Burkitt lymphoma including the roles of the associated Plasmodium falciparum malaria and EBV infections. Comprehensive sequencing set includes genomic, transcriptomic, and epigenomic datasets in concert with variable clinical phenotypes and outcome information such as anatomical presentation site, in-hospital survival rates, and EBV genome type. This deposit includes additional small RNA-seq data from endemic BL (eBL) tumors and RNA-sequencing data from sorted NK cell subsets from the peripheral blood of eBL patients. The additional small RNA-seq data are from tumor specimens from 17 eBL cases, of the previously deposited polyA RNA-seq data from 28 eBL cases (phs1282.V1). The additional RNAseq data from Fluorescence-activated cell sorting (FACS) of NK cell subsets, isolated from the peripheral blood of 7 eBL cases. The additional RNAseq data are from eBL tumor samples of 5 eBL cases, BL cell lines established from these tumor samples and also NSG mouse tumors created by implanting the established BL cell lines into NSG mice. The dataset also includes RNAseq data of the NSG mouse tumors after treatment with Rituximab (RIT) and Phosphate buffered saline (PBS). The fifth batch of data includes mRNA-seq from different passages of a single eBL cell line that have variable EBV phenotypes (low passage with lytic EBV and high passage with latent EBV). This batch also includes lytic and latent lymphoblastoid cell line (LCL) clones from a single blood donor generated through infection with the strain of EBV isolated from the aforementioned eBL cell line. For initial transcriptome analysis see: Kaymaz et al. "Comprehensive Transcriptome and Mutational Profiling of Endemic Burkitt Lymphoma Reveals EBV Type-specific Difference." Molecular Cancer Research, 2017, PMID: 28465297. For initial microRNA analysis see: Oduor et al. "Human and Epstein-Barr Virus miRNA Profiling as Predictive Biomarkers for Endemic Burkitt Lymphoma." Frontiers in Microbiology 8, 2017, PMID: 28400759. For initial NK subsets RNA expression analysis see: Forconi et al. "A new hope for CD56negCD16pos NK cells as unconventional cytotoxic mediators: an adaptation to chronic diseases." Frontiers in Cellular and Infection Microbiology, 2020, PMID: 32373555.For initial eBL cell line and mouse avatar RNA expression analysis see: Saikumar et al. "Endemic Burkitt lymphoma avatar mouse models for exploring inter-patient tumor variation and testing targeted therapies." Life Science Alliance, 2023, PMID: 36878637. For general overview of cohort study see: Buckle et al. "Factors influencing survival among Kenyan children diagnosed with endemic Burkitt lymphoma between 2003 and 2011: A historical cohort study." Int J Cancer. 15:1231, 2016, PMID: 27136063.

Study phs001282

Gabriella Miller Kids First Pediatric Research Program in Enchondromatoses and Related Malignant Tumors

Chondrosarcoma is a malignant tumor that originates from cartilaginous cells. It is the third most common primary malignancy of bone after myeloma and osteosarcoma. It accounts for about 20% of bone tumors and is diagnosed in approximately 600 patients each year in the United States. Up to 40% of the chondrosarcomas arise from an enchondroma. Enchondromas are benign, intramedullary cartilaginous tumors of bone. They can be solitary or multiple and are present in >3% of the population. Enchondromatosis refers to a group of diseases characterized by multiple enchondromas including metachondromatosis (MC), Ollier disease (OD), and Maffucci syndrome (MS) among others. All have skeletal abnormalities with or without associated vascular anomalies that can cause severe limb deformities during early childhood. The risk for chondrosarcoma is up to 30% in OD and MS. Currently, the only treatment for patients with these disorders is surgical; there is no effective pharmacologic therapy. The molecular bases of these two conditions is not well understood.

Study phs001987

GOSH_Tumour_Embryology_Paediatric_Behjati_RNA_Managed_Access

The aim of the study is to study thyroid development and function, and how this is altered in Down Syndrome and Thyroid Cancer.

Study EGAS00001006737

Genomic landscape of malignant peripheral nerve sheath tumor (MPNST)

Neurofibromatosis type 1 (NF1) is the most common tumor predisposition syndrome, and is associated with an aggressive soft-tissue sarcoma, malignant peripheral nerve sheath tumours (MPNSTs), the greatest cause of morbidity and mortality in people with NF1. The only potentially curative therapy involves surgery which is not always possible. Even therapy with curative intent is associated with poor overall survival for both sporadic and NF1-related MPNSTs. The development of novel therapies has been largely hindered by a lack of understanding of the molecular events underpinning MPNST pathogenesis. This is a comprehensive multi-omic study of MPNST evolution based on whole genome sequencing and transcriptomic data.

Study EGAS00001006069

Single_Cell_Targeted_Sequence_Capture

This study is to ascertain whether it is feasible to extract single cell from a tumour, perform amplification, generate a library and sequence a targeted pulldown.

Study EGAS00001000435

NHLBI TOPMed: Early-Onset Atrial Fibrillation in the Estonian Biobank

The Estonian Biobank is the population-based biobank of the Estonian Genome Centre of University of Tartu. The biobank is conducted according to the Estonian Gene Research Act and all participants have signed broad informed consent. The cohort size is currently 51,535 people from 18 years of age and up.

Study phs001606

Metabolism and Genetics of Hypobetalipoproteinemia

Hypobetalipoproteinemia is characterized by extremely low levels of low-density lipoprotein cholesterol. Familial hypobetalipoproteinemia (FHBL) is a monogenic form of hypobetalipoproteinemia caused by mutations in the APOB gene. There are cases of hypobetalipoproteinemia not caused by mutations in APOB, however. The purpose of this study is to identify novel genetic causes of hypobetalipoproteinemia.

Study phs000561

Long read transcriptome of DM1 patients whole blood

DM1 is characterized by dysregulation of alternative mRNA splicing, to an quantitative as well as qualitative extend that is heterogenous between clinically similar patients. Hundreds of transcripts have been identified that can be misspliced in DM1, and for many of these it is still unclear whether they generate stable proteins in DM1 patients. We generated long-read transcriptome data of DM1 patients whole blood after hemoglobin depletion. Each sample is a mix of 5 patients of varying age.

Study EGAS50000000196

The 5-hydroxymethylcytosine Landscape of Prostate Cancer

This dataset consists of genome-wide 5hmC methylomes at various stages of prostate cancer, including not only 93 metastases from castration-resistant prostate cancer (mCRPC) patients, but also 5hmC patterns in cell-free DNA (cfDNA). There are 2000 runs in total as fastq files.

Dataset EGAD00001008462

59 CLPD-NK cases WGS & WTS data

For the cohort of 59 samples, we performed TruSeq DNA PCR-Free whole-genome sequencing library preparation according to manufacturer’s instructions (llumina, ILMN, San Diego, CA) on the automated NGS Star liquid handling platform (Hamilton, Bonaduz, Switzerland) followed by 2x150 bp paired-end sequencing on the HiSeqX or NovaSeq6000 (ILMN). An average coverage of >100x was achieved. For whole transcriptome analysis, the TruSeq Total Stranded RNA kit was used, starting with 250 ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (ILMN). 2x100bp paired-end reads were sequenced on the NovaSeq 6000 with a median of 50 mio. reads per sample (ILMN).

Dataset EGAD00001008558

TB-DAR Whole Genome Sequencing Study

116 Whole Genome Sequencing (WGS) samples from the TB-DAR study, based on a cohort of adult pulmonary tuberculosis patients recruited in Dar es Salaam, Tanzania. WGS was performed at the Health2030 Genome Center in Geneva on the Illumina NovaSeq 6000 instrument (Illumina Inc, San Diego CA, USA), starting from1μg of whole blood genomic DNA and using Illumina TruSeq DNA PCR-Free reagents for library preparation and the 150nt paired-end sequencing configuration. Average coverage was above 30X for 75 samples, between 10X and 30Xfor 40 samples, and approximately 8X for a single sample. Sequencing reads were aligned to the GRCh38 (GCA_000001405.15) reference genome using bwa (Version 0.7.17).

Dataset EGAD00001008400

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95632B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 626 samples; filetype=bam

Dataset EGAD00001004748

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95624A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 604 samples; filetype=bam

Dataset EGAD00001004747

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95622A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 509 samples; filetype=bam

Dataset EGAD00001004746

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95621B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 488 samples; filetype=bam

Dataset EGAD00001004745

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90706

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 522 samples; filetype=bam

Dataset EGAD00001004744

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90694B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

Dataset EGAD00001004743

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90694A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 493 samples; filetype=bam

Dataset EGAD00001004742

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95632D

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples; filetype=bam

Dataset EGAD00001004749

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95660A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1522 samples; filetype=bam

Dataset EGAD00001004750

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 465 samples; filetype=bam

Dataset EGAD00001004751

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 606 samples; filetype=bam

Dataset EGAD00001004752

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 615 samples; filetype=bam

Dataset EGAD00001004753

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 636 samples; filetype=bam

Dataset EGAD00001004754

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95722A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 968 samples; filetype=bam

Dataset EGAD00001004755

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 480 samples; filetype=bam

Dataset EGAD00001004756

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 561 samples; filetype=bam

Dataset EGAD00001004757

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 928 samples; filetype=bam

Dataset EGAD00001004759

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples

Dataset EGAD00001004760

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95736A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1072 samples

Dataset EGAD00001004761

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96139A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1436 samples; filetype=bam

Dataset EGAD00001004762

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96145A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 589 samples; filetype=bam

Dataset EGAD00001004763

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96150A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 656 samples; filetype=bam

Dataset EGAD00001004764

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 648 samples; filetype=bam

Dataset EGAD00001004765

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 375 samples; filetype=bam

Dataset EGAD00001004766

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96165A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 755 samples; filetype=bam

Dataset EGAD00001004767

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96171A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 492 samples; filetype=bam

Dataset EGAD00001004768

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires forlibrary A96176A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 531 samples; filetype=bam

Dataset EGAD00001004769

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96187A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

Dataset EGAD00001004770

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90689C

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 718 samples; filetype=bam

Dataset EGAD00001004741

Whole genome sequencing of 198 epileptic individuals.

This dataset includes whole genome sequencing of 198 epileptic individuals. Libraries preparation and whole-genome sequencing: gDNA was cleaned up using ZR-96 DNA Clean & ConcentratorTM-5 Kit (Zymo) prior to being quantified using the Quant-iTTM PicoGreen dsDNA Assay Kit (Life Technologies) and its integrity assessed on agarose gels. Libraries were generated using the TruSeq DNA PCR-Free Library Preparation Kit (Illumina) according to the manufacturer‚Äôs recommendations. Libraries were quantified using the Quant-iTTM PicoGreen dsDNA Assay Kit (Life Technologies) and the Kapa Illumina GA with Revised Primers-SYBR Fast Universal kit (Kapa Biosystems). Average size fragment was determined using a LabChip GX (PerkinElmer) instrument. The libraries were denatured in 0.05N NaOH and diluted to 8pM using HT1 buffer. The clustering was done on a Illumina cBot and the flowcell was ran on a HiSeq 2500 for 2x125 cycles (paired-end mode) using v4 chemistry and following the manufacturer's instructions. A phiX library was used as a control and mixed with libraries at 0.01 level. Bioinformatics: The Illumina control software was HCS 2.2.58, the real-time analysis program was RTA v. 1.18.64. Program bcl2fastq v1.8.4 was used to demultiplex samples and generate fastq reads. The filtered reads were aligned to reference Homo_sapiens assembly b37. Each readset was aligned to creates a Binary Alignment Map file (.bam).

Dataset EGAD00001004062

Cancer Single Cell Sequencing

This study is to ascertain whether it is feasible to extract a single cell form a Cancer cell line, amplify it and sequence it.

Study EGAS00001000003

Illumina HumanCoreExome genotyping data from the British Society for Surgery of the Hand Genetics of Dupuytren’s Disease consortium (BSSH-GODD consortium) collection

Dupuytren's Disease (DD - OMIM126900) is the most common heritable disorder of connective tissue. It is a fibroproliferative disorder of the palmer fascia, causing flexion contractures of affected digits. DD affects men more commonly than women. DD is an archetypal complex disease, with multiple genetic and environmental factors affecting the final expression of the disease phenotype. The incidence increases with age, and the prevalence of DD is therefore increasing as the UK population ages. Half of all patients present before age 60. DD causes significant functional impairment, and severe contractures can lead to permanent disability. The mainstay of current treatment is surgery, but recurrence and complications are both high. For severe contractures, the only suitable treatment option is amputation. The direct costs to the NHS are high, and underestimate the true economic costs to society. We collected salivary samples from adults in the UK who have had surgery for DD. We have genotyped these samples using the Illumina HumanCoreExome Beadchips. https://research.ndorms.ox.ac.uk/public/dupuytrens/what-is-dupuytrens-disease/

Study EGAS00001001206

Adult-type Granulosa Cell Tumour of the Ovary

A recurrent mutation in FOXL2 (c.402C>G; p.C134W) is present in over 95% of adult-type granulosa cell tumours (AGCTs). In contrast, various loss-of-function mutations in FOXL2 lead to the development of blepharophimosis, ptosis and epicanthus inversus syndrome (BPES). BPES is characterized by an eyelid malformation often accompanied with primary ovarian insufficiency but not granulosa cell tumours. Two recent studies suggest that FOXL2 C402G is a gain or change-of-function mutation with altered DNA-binding specificity. Another study proposes that FOXL2 C402G is selectively targeted for degradation inducing somatic haploinsufficiency suggesting its role as a tumour suppressor. The latter study relies on data indicative of an FOXL2 allelic imbalance in AGCTs. Here we present RNA-seq data as genetic evidence that no real allelic imbalance is observed at the transcriptomic level in AGCTs. Additionally, there is no loss of protein expression in tumours harboring the mutated allele. These data and other features of this mutation as compared to other oncogenes and tumour suppressor genes argue strongly against FOXL2 being a tumour suppressor in this context. Given the likelihood that FOXL2 C402G is oncogenic, targeting the variant protein or its downstream consequences is the most viable path forward to identifying an effective treatment for this cancer.

Study EGAS00001005414

LungMAP: Molecular Atlas of Lung Development - Human Lung Tissue

Mammalian fetal lung development is a complex biological process. Despite considerable progress, a comprehensive understanding of the dynamic regulatory networks that govern postnatal alveolar lung development is still lacking. The purpose of this study as part of the LungMAP consortium (www.lungmap.net) is to understand the transcriptional changes in the process of mammalian lung development.

Study phs001961

16S-based fecal microbiota composition of the Milieu Intérieur Cohort

The Milieu Intérieur project is a population-based study coordinated by the Institut Pasteur, Paris. The objective is to dissect the interplay between genetics and environment and their impact on the immune system. One of the primary goals of the project is to ascertain the role of the microbiota in regulating immune programs.

Study EGAS00001003419

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