1073 results for "2025年12月600642股价走势分析"

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• Dataset contains all Single cell RNAseq data of human neurons from the study Bouwen et al Nat Comm 2025

  These documents contain the patch seq data presented in the Bouwen et al Nat Comm 2025. Human brain samples were gathered during surgery, neurons were isolated using patch clamp glass pipette. Isolated cells were processed using Smartseq2 pipeline, and sequenced using an Illumina 2500. Files are formatted in fastq format. There are a total of 12 patient samples, each with 2 replication runs.

  Dataset EGAD50000001979

• Ultra-long whole-genome and Cas9-targeted nanopore sequencing of fibroblasts: FSHD, BAMS, healthy controls

  Data from the D4Z4End2End study (Xiao et al. 2025), for genetic and epigenetic analysis of the D4Z4 macrosatellite in health and disease.

  Dataset EGAD50000001551

• NAR-GAB 2025 deposit data

  Human exome gVCFs: rare-disease cohort for the NAR-GAB 2025 study on splicing-SNV prioritization.

  Study EGAS50000001456

• Thymic epithelial transplantation for complete DiGeorge syndrome Spatial (2025-07-28)

  Spatial transcriptomics study of thymic transplant biopsies . This dataset contains all the data available for this study on 2025-07-28.

  Dataset EGAD00001015659

• Thymic epithelial transplantation for complete DiGeorge syndrome: RNA (2025-10-02)

  Single cell transcriptomics study of thymic transplant biopsies . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015721

• Genotype-Tissue Expression (GTEx) (2025-07-28)

  Dual snRNAseq and ATACseq of replicate PBMC samples for 10X beta testing. . This dataset contains all the data available for this study on 2025-07-28.

  Dataset EGAD00001015663

• Engineered cartilage: deriving design principles from human developmental pathways (2025-10-02)

  Engineered cartilage: deriving design principles from human developmental pathways . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015724

• Engineered cartilage: deriving design principles from human developmental: RNA (2025-07-30)

  Engineered cartilage: deriving design principles from human developmental pathways . This dataset contains all the data available for this study on 2025-07-30.

  Dataset EGAD00001015664

• Spatially resolved cellular and molecular drivers of cardiac remodelling in healthy and failing human hearts: Adult DNA (2025-10-16)

  Human Cell Atlas - WGS Adult Heart . This dataset contains all the data available for this study on 2025-10-16.

  Dataset EGAD00001015751

• Spatially resolved cellular and molecular drivers of cardiac remodelling in healthy and failing human hearts: Adult Spatial (2025-07-31)

  Spatial transcriptome analysis of the human heart . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015666

• A study of the immune system in patients with peripheral inflammatory neuropathy (CIDP): RNA adult (2025-10-02)

  Leveraging single-cell sequencing technologies to shed light on the immune aetiology of chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015725

• Genomic and transcriptomic determinants of host susceptibility, protection, and viral mutation in experimental SARS CoV-2 infection: RNA (2025-08-11)

  Single-cell profiling of healthy adult volunteers that were inoculated with SARS-CoV-2. . This dataset contains all the data available for this study on 2025-08-11.

  Dataset EGAD00001015679

• Transcriptomic profiling of the Enteric Nervous System in Hirschsprung Disease (2025-07-31)

  This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015667

• MASS_Pilot: Muscle and Ageing Science Study - Collaboration with Wellcome Sanger Institute to characterise skeletal muscle ageing using Human Cell Atlas approaches (2025-07-31)

  Transcriptomic analysis of skeletal muscle, to understand the mechanisms of muscle ageing. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015670

• Fluctuating DNA methylation tracks cancer evolution at clinical scale

  Long-read Nanopore data of fCpGs from Gabbutt & Duran-Ferrer (2025) for developing the EVOFLUx method to study cancer evolution via DNA methylation fluctuations.

  Study EGAS50000001192

• Sahel Data Access Committee

  Genome-wide genotype array data of Fulani populations presented in Fortes-Lima et al. 2025. Citation: Population History and Admixture of the Fulani People from the Sahel. Cesar A. Fortes-Lima, Mame Y. Diallo, Václav Janoušek, Viktor Černý, and Carina M. Schlebusch. American Journal of Human Genetics 112(2), February 6, 2025. doi: https://doi.org/10.1016/j.ajhg.2024.12.015

  Dac EGAC50000000290

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Paediatric Spatial (2025-07-31)

  This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015665

• Bouwen Gao Nat Comm 2025

  Single cell sequencing results

  Dac EGAC50000000783

• The EGA Helpdesk team: 2025 in review and what we are building next

  Behind every dataset submitted, every access request processed, and every technical question answered, there is a team working quietly to keep things moving: the Helpdesk (HD). With the onset of 2026, this feels like the right moment to look back on what 2025 has been like for the HD team: the challenges we faced, how we adapted, and where we're heading next. Why the Helpdesk matters to EGA The EGA Helpdesk is more than a support channel. It plays a key role in maintaining trust in the EGA ecosystem. By supporting data submitters, researchers, Data Access Committees (DACs), and institutional partners, the HD helps ensure that data can flow securely, efficiently, and reliably. When issues arise, the Helpdesk is often the first place where their impact is felt and addressed. In that sense, the HD sits at the intersection of technology, policy, and people. One Helpdesk, two locations, one shared mission The EGA Helpdesk is a joint, distributed team working closely across two locations: CRG (Barcelona, Spain) and EMBL-EBI (Cambridge, UK). Although we are based in different institutions, we operate as a single Helpdesk, with shared workflows, priorities, and responsibility towards users. At CRG, the HD team is formed by: Andrea Max Àlex and me At EMBL-EBI, we work closely with: Silvia Coline Aravind What defines us as a team is simple: we work user-first, even under pressure. In a highly technical environment, clarity, empathy, and consistency matter just as much as tools and processes. A close collaboration across sites is essential to making that happen. What does the EGA Helpdesk do? The HD supports users across the full lifecycle of data in EGA. This includes: Data submissions, uploads, and encryption workflows. Data access requests and permissions. Questions around policies, consent, and data usage. Technical and system-related issues. Coordination between users, internal teams, and external partners. 2025: growth, change, and recalibration 2025 was a year of growth, but not always a predictable one. Early in the year, several technical and system-related challenges required us to adjust our original plans. Priorities shifted, timelines changed, and some improvements had to be rethought. For the HD team, this is often the hardest part of the job: we see delays through the eyes of users and understand the real impact they can have on ongoing research. One of the key lessons from 2025 was that stability is not only a technical challenge, but also an organisational one. Teamwork proved to be essential: anticipating peak periods, sharing context early, and coordinating closely across teams made a tangible difference. When things became complex, working together across roles and locations was what allowed us to keep moving forward. In 2025, the Helpdesk received 5.313 tickets and resolved 5.511 requests, reflecting both increased adoption of EGA and the team’s ability to absorb higher demand. At the same time, demand continued to grow. Compared to 2024, ticket creation increased by over 6%, while resolution capacity grew by more than 11%. The team not only kept up with incoming requests but also resolved part of the accumulated backlog, finishing the year having solved more tickets than were created. The real challenge of 2025 was not overall performance, but how the workload was concentrated during peak months. Seasonality and demand spikes placed pressure on the system, even while overall efficiency remained strong. On a team level, 2025 was also a year of transition. I joined the HD leadership role in January 2025, stepping into a period of change and rapid learning. Later in the year, in October, we said goodbye to Raül, and in January 2026, we welcomed Àlex, strengthening the team for the next phase. What users needed most in 2025 While requests vary widely, some themes stood out throughout the year: Support with data submissions and uploads Data access requests and permissions Technical and system-related issues As EGA matures, day-to-day operations have become more complex. Many long-running tickets are not delayed due to a lack of follow-up, but because they depend on external approvals, cross-institutional coordination, or multi-step processes. Understanding these patterns helps us focus not just on resolving tickets, but on improving how work flows through the system. Looking ahead to 2026 With a reinforced team and clearer insights from 2025, our focus for 2026 shifts from throughput to flow. Key priorities include: Strengthening our web content and documentation Reducing structural backlog Improving cross-team and cross-system coordination Anticipating peak demand earlier and planning capacity accordingly Challenges will continue to arise in 2026, as they always do. However, 2025 reinforced something important: a stable, empathetic, and well-aligned Helpdesk team is essential to supporting EGA's mission at scale. Supporting users well means supporting research, and that remains at the core of what we do.

  Blog ega-helpdesk-team-2025-in-review-and-upcoming-improvements

• Spatially resolved cellular and molecular drivers of cardiac remodelling in healthy and failing human hearts: Adult RNA (2025-07-31)

  Cell Atlas of the diseased human heart. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015668

• REL-2017-07-2025

  HipSci - Congenital Hyperinsulinia - Expression Array - July 2017

  Dataset EGAD00010001378

• Diseased heart analysis: RNA Adult (2025-10-14)

  Samples for this project are taken from adult human hearts which have been preserved using 2 different methods (cold static storage on ice, and hypothermic perfusion). Samples have been acquired at various time points during post-preservation normothermic perfusion. The aim of the project is to assess the transcriptional changes caused by these differing methods of preservation. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015738

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015718

• Whole-genome sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumoroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015707

• Single-cell RNA-sequencing of rhabdomyosarcoma tumouroids (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumouroids data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015708

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015709

• Bulk RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the bulk RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015714

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015716

• Cardiac fibroblast DAC

  DAC for reviewing requests to access data on cardiac fibroblasts as described by Aguado-Alvaro et al (Nature Communications, 2025)

  Dac EGAC50000000479

• WES to explore mutational landscape of blood and non blood liquids in female patients with metastatic breast cancer.

  Whole Exome Sequencing (WES) to explore mutational landscape of blood and non blood liquids in female patients with metastatic breast cancer. 11 patients. 86 liquid samples, 11 matched normal samples. Median coverage 67X. Illumina paired-end sequencing. Fastq files are provided. WES from Richard et al., Nature Communications, 2025 low-pass Whole Genome Sequencing (lpWGS) to assess the representativeness of seven body liquids from female patients with metastatic breast cancer. 216 liquid samples, 745 solid samples, 20 matched normal samples. 0.5X coverage. lpWGS from Richard et al., Nature Communications, 2025.

  Dataset EGAD50000001852

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• Lung Cell Atlas: Paediatric RNA (2025-10-02)

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015722

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715

• Lung Cell Atlas: Paediatric Spatial (2025-10-02)

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015723

• WGS data from MTB-Guided Targeted Treatments paper

  WGS data from biliary tract cancer samples (Beaudry et al, 2025; n=55)

  Dataset EGAD50000001418

• Whole Genome-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the whole-genome sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015712

• Walter and Eliza Hall - Aix-Marseille Université

  Data Access Committee for the Liao et al. 2025 study, D4Z4End2End: complete genetic and epigenetic architecture of D4Z4 macrosatellites in FSHD, BAMS and reference cohorts.

  Dac EGAC50000000655

• Single cell RNAseq data of human neurons, Bouwen et al Nat Comm 2025

  Brain tumor patients often suffer from epilepsy, but the underlying neuronal changes leading to this neurological symptom are not well understood. This study examined the transcriptomic profiles of human cortical neurons collected from brain tumor patients with or without seizures. The goals of the study were to identify the molecular identities of the recorded neurons and confirm that they are layer 2/3 pyramidal neurons rather than neuron-like tumor cells; and to compare the differential gene expression profiles between patients with and without epilepsy. For each patient, cortical neurons were rapidly isolated from surgically resected tissue and prepared using the Smart-seq2 protocol. Samples from 12 patients were sequenced on an Illumina HiSeq 2500 platform to generate their transcriptomic profiles.

  Study EGAS50000001369

• SUM-seq data for spontaneously differentiated iPSCs to EBs

  Clonal CRISPRi/a hiPS cell lines were plated to induce spontaneous differentiation in KSR medium (KSR medium: knockout DMEM/F12 (Gibco, 12660012), 2 mM GlutaMAX, 1× NEAAs, 20% knockout serum replacement (Gibco, 10828010) and 0.1 mM β-mercaptoethanol (Merck-Millipore)). non-TC plates and dishes were used. At the day of plating, KSR medium was supplemented with Y-27632 (10 µM). The next day, medium was replaced with fresh KSR medium. Medium changes were performed every other day. EBs were transferred to 15 ml conical tubes and allowed to sediment at room temperature for 5 min. The supernatant was replaced with fresh KSR medium and cells were transferred onto non-TC treated plates and maintained at 37 °C, 5% CO2. On day 12 of differentiation, the KSR medium was replaced with Essential 6 medium (Gibco, A1516401). EBs were collected and subjected to SUM-seq library preparation as described in Lobato-Moreno et al. 2025 Nature Methods.

  Dataset EGAD50000001589

• Sequenced IDH wildtype, untreated, human glioblastoma samples (GB-UK cohort)

  BAM files for 42 IDH wildtype, untreated, human glioblastoma samples from the GB-UK cohort, published in Noorani & Haughey et al. Cancer Discovery (2025).

  Dataset EGAD50000001649

• DAC for Liquid CNA in High Grade Serous Ovarian Cancer

  Low pass sequencing of sequential cell free and tumour DNA with matched whole genome sequencing from five patients with high grade serous ovarian cancer presented in Hockings et al Cancer Research paper, 2025.

  Dac EGAC50000000648

• Organ maturation in preparation for birth (Peds RFA) to develop a tissue resource and a single-cell atlas of organ development and maturation for dissemination among the scientific and clinical community: RNA (2025-10-14)

  Knowledge about abnormal organ development is important to understand pathology and to develop novel treatment approaches for individuals with congenital and acquired disease. Most of our current understanding is based on examination of tissues from the embryo and early foetus, collected from women undergoing termination of pregnancy in the first trimester (third) of pregnancy. There is very little known about normal and abnormal organ development from a developmental perspective during the crucial last two-thirds of pregnancy when much remodelling of foetal tissues occurs. This study will generate a single-cell atlas of late-foetal lungs, blood, heart, bone and immune organs. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015737

• WGS data from COMPASS Trial

  WGS data for pancreatic cancer samples (COMPASS Trial; Knox et al., Journal of Clinical Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=263 tumour/normal pairs).

  Dataset EGAD50000001832

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015713

• Long-read Nanopore data EVOFLUx

  Bam files with all reads covering 976 fCpGs identified in Gabbutt and Duran-Ferrer 2025 to develop the EVOFLUx methodology. These include 10 samples, 6 normal B cells, and 2 CLL patients developing RT.

  Dataset EGAD50000001697

• WGS data for Pancreatic Cancer samples (misc.)

  WGS data for pancreatic cancer samples. These are miscellaneous samples which are part of a tandem duplicator phenotype paper (Farooq et al, NPJ Precision Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina NovaSeq 6000 and aligned against GRCh38 (n=7 tumour/normal pairs).

  Dataset EGAD50000001833

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Adult RNA (2025-10-14)

  Animal studies have demonstrated that resident memory T (Trm) cells provide enhanced protective responses to a broad array of tissue-tropic pathogens, thus making Trm cells promising targets for novel vaccination strategies. However, the biological pathways that enable the long-term survival of Trm cells are poorly understood in humans. Here, we will employ a unique human intestinal transplantation setting that allows us to study the retention of persistent T cells in the grafts and the temporal development of resident T-cell populations from recruited recipient T cells. We will integrate high resolution transcriptomics, epigenetics, proteomics and immune repertoire single-cell data from purified intestinal T cells. These single-cell multiomics approaches will uncover the diversity and differentiation of the T cell populations in the human intestine, allowing us to temporally resolve the generation and maintenance of gut resident T cells. . This dataset contains all the data available for this study on 2025-10-14.

  Dataset EGAD00001015739

• Data from Shea et al Can Research 2025

  This dataset contains single cell RNA sequencing (192 fastq files for 59 samples), whole exome sequencing (20 BAM files -hg38- for 20 samples) and bulk RNA sequencing (138 paired-end fastq files and 17 single-end fastq files for 8 samples)

  Dataset EGAD50000001334

• Comparison of transcriptomics profile of stem cell-derived beta cells from HUES8 and RC9

  Stem cell-derived islet cells have a potential to be used to restore endogenous insulin production in people with diabetes. The goal of this experiment is to compare the transcriptomics profile of stem-cell derived beta cells from two different cell lines: HUES8 (non-clinical grade) and RC9 (clinical grade) in terms of beta cell identity and maturity. Stem cell-derived islets were produced using differentiation protocol detailed in Rajaei et al. 2025 (manuscript approved in Science Translational Medicine, pending pubmed ID). Single cell transcriptomics data were generated using 10x Genomics 3' Single Cell Gene Expression kit.

  Study EGAS50000000905

• lpWGS of solid and liquid samples from female patients with metastatic breast cancer

  low-pass Whole Genome Sequencing (lpWGS) to assess the representativeness of seven body liquids from female patients with metastatic breast cancer. 20 patients. 216 liquid samples, 745 solid samples, 20 matched normal samples. 0.5X coverage. Illumina single read sequencing. Fastq files are provided. lpWGS from Richard et al., Nature Communications, 2025.

  Dataset EGAD50000001851

• Learning from the thymic human cell atlas for T cell engineering: Paediatric RNA (2025-10-02)

  T cells are central to adaptive immunity and thus crucial for understanding and treating human disease. While extensively studied in model organisms, translating this knowledge to humans can sometimes be limited by their rapid cross-species evolution and diverse . This dataset contains all the data available for this study on 2026-03-10.

  Dataset EGAD00001015720

• A next-generation dual guide CRISPR system for genetic interaction library screening

  Raw sgRNA sequencing data from a pilot CRISPR screening library to test the dual guide vector system (8,914 guide pairs), and from a large scale genetic interaction screen (~100,136 guide pairs) in HT-29 cells. This data refers to Burgold et al. Nature Communications 2025.

  Dataset EGAD00001015754

• Purified vs unpurified stem cell-islets

  A scRNAseq dataset consisting of stem cell-derived islets treated with gradient separation (HUES8_Pure_Islets) and unpurified control (HUES8_control_islets). scRNAseq was done on cryopreserved stage 7 stem cell (HUES8 cell line)-derived islets. Details about stem cell differentiation and sequencing can be found on the publication by Rajaei et al. (2025, Science Translational Medicine). This dataset correspond to Fig 4 of the publication.

  Dataset EGAD50000001396

• Mapping Cells and Interactions in the Thymus Across Development and Aging (2025-07-28)

  Single cell RNA sequencing on thymic cells from children with syndromic diseases such as Trisomy 21 and inflammatory/autoimmune diseases such as myasthenia gravis. Our group has previously performed atlasing of the healthy human thymus using single cell transcriptomics and obtained an unprecedented understanding of human thymus throughout development. In this study, we intend to survey diseased human thymus and compare this to healthy to obtain a better understanding of thymic dysfunction in human diseases. The diseases we will survey include congenital conditions such as Down's syndrome, CHARGE syndrome, DiGeorge syndrome as well as acquired diseases such as myasthenia gravis and thymic hyperplasia. We intend to perform genetic and genomic study on the samples, including expression analysis. This will not only help us to understand the cells and molecular pathways affected in dysfunctional thymus; but may also lead to generalisable understandings in human genetic diseases and inflammatory/autoimmune diseases. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2025-07-28.

  Dataset EGAD00001015660

• Head and Neck Organoid Biobank cohort, Issing et. al., 2025, RNA + WES data

  This dataset contains the raw fastq files of RNA and whole exome sequencing of the head and neck organoid biobank. For RNA sequencing, 41 organoid samples collected at different timepoints as well as before and after genetic modification are included. For WES, 25 samples of early organoid cultures or matching tumor tissues are included.

  Dataset EGAD50000001733

• Shallow whole genome sequencing DETECT samples

  Shallow whole genome sequencing of samples from the paper Beddowes et al. A large-scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression-free survival. Mol. One 2025. This includes 1048 longitudinal plasma samples from 149 patients and 35 normals. Samples were sequenced with shallow whole genome sequencing for copy number estimation. All the files are single-end fastq files.

  Dataset EGAD50000001333

• Sequence data for "An allele-resolved nanopore-guided tour of the human placental methylome" (Kindlova et al 2025)

  Sequence data generated for the study "An allele-resolved nanopore-guided tour of the human placental methylome" includes Illumina WGS, Illumina RNA-seq, Illumina EM-seq, and Oxford Nanopore Technologies PromethION sequence data.

  Dataset EGAD50000001850

• WTS data from PASS-01 trial

  WTS data for pancreatic cancer samples (PASS-01 Trial; Knox et al., Journal of Clinical Oncology, 2025).  The dataset includes tumour bam files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=115 tumours)

  Dataset EGAD50000002308

• WGS data from PASS-01 trial

  WGS data for pancreatic cancer samples (PASS-01 Trial; Knox et al., Journal of Clinical Oncology, 2025).  The dataset includes tumour and normal cram files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=127 tumour/normal pairs)

  Dataset EGAD50000002309

• stem cell-derived beta cells from cell lines RC9 and HUES8

  stem cell-derived beta cells differentiated using two different cell lines: HUES8 (non-clinical grade) and RC9 (clinical grade). iPSC stem cell lines were differentiated to pancreatic islets using differentiation protocol as detailed by Rajaei et al. (2025, Science Translational Medicine, accepted for publication). scRNAseq was done at stage 7 of differentiation (day 30) using 10X genomics 3' sequencing. Cells were annotated then subsetted for beta cells for downstream analysis

  Dataset EGAD50000001322

• WGS data for Pancreatic Cancer samples (resection cohort)

  WGS data from pancreatic cancer samples. These are part of a resected cohort from a tandem duplicator phenotype paper (Farooq et al, NPJ Precision Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=189 tumour/normal pairs).

  Dataset EGAD50000001834

• NAR-GAB 2025 deposit data

  Paired-end whole-exome sequencing data derived from Illumina hybrid-capture experiments (Agilent SureSelect Human All Exon kits). Six human probands with rare diseases; one sample per subject. Sequencing reads from each individual were processed into analysis-ready gVCF files following standard best-practice pipelines, including alignment, duplicate marking, base quality calibration, and variant calling. All gVCF files are encrypted using Crypt4GH and are available under controlled access through our DAC in accordance with a strict DUO-based policy.

  Dataset EGAD50000002100

• To profile the landscape of sebaceous tumours_WES

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract DNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted DNA will be used for exome sequencing. Please note that the dataset was last revised on October 16, 2025.

  Dataset EGAD00001015367

• Admixture histories of São Tomé e Príncipe.

  Genotyping datasets used in the article "Nested admixture during and after the Trans-Atlantic Slave Trade in the island of Sao Tome" by Ciccarella M et al. 2025 The genotype data corresponds to 2,104,148 autosomal SNPs genotyped from the IlluminaOmni 2.5 Million BeadChip for 97 volunteer participants sampled on São Tomé e Príncipe, family unrelated at the 2nd degree based on population genetics analyses. In particular, the dataset is composed of 95 individual samples collected on São Tomé and 2 collected on Príncipe. SNP rsID, Chromosome position and genetic position in (bp) are in Build GRCh38.

  Dataset EGAD50000001348

• Single cell characterization of T-cell lymphoma: RNA (2025-07-31)

  Lymphomas are types of blood cancer derived from lymphocytes, and can be classified into two main categories, Hodgkin's lymphomas (HL) and non-Hodgkin lymphomas (NHL). T-cell lymphoma is a type of NHL that develops from T lymphocytes and accounts for 10-15% of total NHL cases. As a rare disease, T-cell lymphoma is functionally, pathologically, and clinically complex and heterogeneous. The 2016 revision of the WHO classification has listed 29 subtypes of mature T/NK-cell neoplasms, among which over 25 are T lymphocyte in origin. These subtypes of T-cell lymphomas have different biological behaviours and clinical prognosis. Clinically, T-cell lymphoma ranges from indolent (slow-growing) to aggressive (fast-growing and spreading) disease. According to the guideline booklet provided by the Lymphoma Research Foundation (https://lymphoma.org/aboutlymphoma/nhl/), indolent T-cell lymphoma subtypes include adult T-cell leukaemia/lymphoma (ATLL), cutaneous T-cell lymphoma (CTCL), and mycosis fungoides (MF), while the aggressive subtypes include anaplastic large cell lymphoma (ALCL), angioimmunoblastic T-cell lymphoma (AITL), peripheral T-cell lymphoma (PTCL), and T lymphoblastic lymphoma (TLBL). PTCL and ALCL represent the most common subtypes of aggressive T-cell lymphoma whereas TLBL is a rare and aggressive subtype mostly diagnosed in children. In this study, we will use single cell RNA sequencing and single cell multiomic methods three aggressive T-cell lymphoma subtypes (ALCL, PTCL and TLBL) and try to gain a deeper insight into the genotypic and phenotypic features of these T-cell lymphomas. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015669

• 12 Nasopharyngeal carcinoma patients without treatment and 12 Nasopharyngeal carcinoma patients with treatment (WGS)

  12 Nasopharyngeal carcinoma patients without treatment and 12 Nasopharyngeal carcinoma patients with treatment (WGS)

  Dataset EGAD00001009840

• Targeted capture ctDNA Library CRCQV42Run036-12

  Targeted capture ctDNA Library CRCQV42Run036-12 from patient PBC0003587, plasma 12 month sample

  Dataset EGAD00001010594

• Targeted capture ctDNA Library CRCQV34Run015-12

  Targeted capture ctDNA Library CRCQV34Run015-12 from patient PBC0002108, plasma 12 month sample

  Dataset EGAD00001010378

• RNA sequencing of 12 NSCLC samples from 4 patients at MDACC

  Multi-region RNA sequencing of 12 NSCLC samples from 4 patients at MDACC

  Study EGAS00001005951

• Whole genome sequencing, SNP array and RNA-seq of uveal melanomas

  We conducted whole genome sequencing and DNA SNP array of 12 uveal melanoma genomes and their matched DNA from blood. We also conducted RNA-seq of the 12 tumour samples.

  Study EGAS00001000472

• Mammary cell samples from donors 28/32/33

  Mammary cell samples from donors 28/32/33. Contains 12 MiSeq sequencefiles and 12 alignment files derived from HiSeq runs.

  Dataset EGAD00001001439

• Whole exome sequencing of 12 NSCLC samples from 4 patients at MDACC

  Multi-region WES from 4 NSCLC patients, totaling 12 tumor samples and 4 matched control samples.

  Study EGAS00001005829

• Colorectal-Cancer-Tumor-Spheres-H012-Microarray_Expression

  Gene expression of 12 colon cancer TSCs (sensitive or resistant) after 12h treatment with 3µM NCT02 or DMSO (control) was analyzed using Illumina microarrays (HumanHT-12 v4 BeadChip).

  Dataset EGAD00010001936

• Target Capture Sequencing of 12 patients

  We perfomed target capture DNA sequencing of 12 patients to assess the detailed biological mechanisms of resistance to immune checkpoint inhibitors.

  Study JGAS000589

• WGS of oesophagogastric cancer

  WGS of 12 oesophagogastric cancer samples WGS or 12 matched germline data.

  Dac EGAC50000000890

• SNP_dataset_1

  Tissue samples using Illumina HumanOmniExpress-FFPE-12 v1.0 BeadChip

  Dataset EGAD00010001179

• single-cell RNA-seq Case-Control study of children progressing to Type1 diabetes

  Single-cell RNA sequencing was carried out on four selected PBMC samples of Finnish children at risk of developing Type 1 diabetes and their gender age and HLA matched control children using 10X genomic platform. All four Case children were positive for multiple islet specific autoantibodies and two of them also progressed to clinical disease during the follow up whereas the control children remain negative for all autoantibodies. Age at seroconversion for Case 2, 3, 5, and 9 children is 12, 18, 24, and 18 months, respectively. Age at sampling, in months, for the pairs was as follows (Case/Control): pair 2:24/24; pair 3: 12/18; pair 5: 12/12; pair 9:24/18.

  Study EGAS00001004070

• WGS of oesophagogastric cancer

  Illumina short read WGS of 12 oesophagogastric cancer samples

  Dataset EGAD50000002239

• Employing_single_cell_sequencing_for_detection_of_mutational_signatures_reflecting_on_going_mutagenesis_

  12 single cells will be sequenced from a previously single-cell derived clone of a JSC-1 cell line. Additional 12 single cells are likely to be sequenced from a previously single-cell derived clone of a SW756 line. Both belong to CGP’s panel of approximately 1000 human cancer cell lines.

  Study EGAS00001002679

• 2018_ETO_WGS

  This study includes 12 paired samples of Korean AML-ETO paitients.12 AML-ETO tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001002804

• Combining dasatinib and IFN-α in CML – immunomodulatory effects linked to treatment response and adverse events

  We pooled 100,000 cells from the 12 scRNA+TCRab-seq samples from peripheral blood from three time points (n=4, samples at 0, 3, and 12 months) to understand the landscape of immune subsets in CML during the course of dasatinib+IFN-α treatment

  Study EGAS00001005049

• KRAS Mutations in Multiple Myeloma

  Fastq files for 80 Multiple Myeloma Patients and 12 cell-lines

  Dataset EGAD00001005743

• WGS data of plasma samples from CRC patients

  WGS data of plasma samples from CRC patients (N=12)

  Dataset EGAD00001006419

• Transcriptomic signatures of CD4+ T cells from visceral leishmaniasis (VL) patients

  Bulk RNA-sequencing was performed on CD4+ T cells isolated from the blood of visceral leishmaniasis patients (n = 12) and endemic controls (EC; n = 12). CD4+ T cells were obtained by magnetic-activated cell sorting (MACS). Alterations in the transcripts of T helper (Th) cells during infection were identified.

  Study EGAS00001004152

• Exome sequencing Wilms tumour

  Exome sequencing of lymphocyte DNA from 12 affected individuals from six unrelated, non-syndromic Wilms tumor families.

  Dataset EGAD00001001003

• Targeted capture ctDNA Library CRCQV42Run025-12

  Targeted capture ctDNA Library CRCQV42Run025-12 from patient PBC0003014, saliva sample

  Dataset EGAD00001010478

• Targeted capture ctDNA Library CRCQV42Run051-12

  Targeted capture ctDNA Library CRCQV42Run051-12 from patient PBC0001516, plasma sample

  Dataset EGAD00001010806

• GabonDiv_SNP_genotyping

  Genome-wide SNP genotyping data for 1,235 western Africans by Illumina HumanOmniExpress-12 array, used in the EGAS00001002078 study

  Dataset EGAD00010001209

• Targeted capture ctDNA Library CRCQV34Run007-12

  Targeted capture ctDNA Library CRCQV34Run007-12 from patient PBC0002816, plasma baseline sample

  Dataset EGAD00001010354

• Targeted capture ctDNA Library CRCQV42Run034-12

  Targeted capture ctDNA Library CRCQV42Run034-12 from patient PBC0004173, buffy coat sample

  Dataset EGAD00001010566

• Targeted capture ctDNA Library CRCQV42Run019-12

  Targeted capture ctDNA Library CRCQV42Run019-12 from patient PBC0001295, plasma baseline sample

  Dataset EGAD00001010419

• Targeted capture ctDNA Library CRCQV34Run011-12

  Targeted capture ctDNA Library CRCQV34Run011-12 from patient PBC0002294, plasma baseline sample

  Dataset EGAD00001010366

• Targeted capture ctDNA Library CRCQV42Run033-12

  Targeted capture ctDNA Library CRCQV42Run033-12 from patient PBC0002406, buffy coat sample

  Dataset EGAD00001010551

• Targeted capture ctDNA Library CRCQV42Run047-12

  Targeted capture ctDNA Library CRCQV42Run047-12 from patient PBC0003385, buffy coat sample

  Dataset EGAD00001010724

• Targeted capture ctDNA Library CRCQV42Run028-12

  Targeted capture ctDNA Library CRCQV42Run028-12 from patient PBC0004076, plasma baseline sample

  Dataset EGAD00001010502

• Targeted capture ctDNA Library CRCQV42Run029-12

  Targeted capture ctDNA Library CRCQV42Run029-12 from patient PBC0004173, plasma baseline sample

  Dataset EGAD00001010512

• Targeted capture ctDNA Library CRCQV42Run032-12

  Targeted capture ctDNA Library CRCQV42Run032-12 from patient PBC0001224, buffy coat sample

  Dataset EGAD00001010538