23085 results for "ega"

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• Additional Neuroblastoma whole genome sequencing data

  Additional Neuroblastoma whole genome sequencing data

  Dataset EGAD00001006196

• H3Africa NEEDI SNPs and INDELs

  SNPs and INDELs of novel hereditary neurological disease genes in Mali using Beckman 8800, ABI 3730/3730xl.

  Dataset EGAD00001006295

• Strelka somatic snv vcfs for EGAS00001004572

  Bulk Strelka somatic snv vcfs from tumour-normal analysis in EGAS00001004572

  Dataset EGAD00001006907

• STAG1 and STAG2-ChIP-seq in RAD21-mutant adult acute myeloid leukemia

  STAG1 and STAG2-ChIP-seq in RAD21-mutant adult acute myeloid leukemia

  Dataset EGAD00001015361

• Ovarian cancer EV RNA-seq

  Ovarian cancer EV RNA-seq

  Dataset EGAD00001008972

• Targeted capture ctDNA Library CRCQV34Run002-10

  Targeted capture ctDNA Library CRCQV34Run002-10 from patient PBC0002108, plasma baseline sample

  Dataset EGAD00001010327

• Targeted capture ctDNA Library CRCQV34Run002-11

  Targeted capture ctDNA Library CRCQV34Run002-11 from patient PBC0002429, plasma baseline sample

  Dataset EGAD00001010328

• Targeted capture ctDNA Library CRCQV34Run002-12

  Targeted capture ctDNA Library CRCQV34Run002-12 from patient PBC0002459, plasma baseline sample

  Dataset EGAD00001010329

• Targeted capture ctDNA Library CRCQV34Run002-13

  Targeted capture ctDNA Library CRCQV34Run002-13 from patient PBC0002595, plasma baseline sample

  Dataset EGAD00001010330

• Targeted capture ctDNA Library CRCQV34Run002-6

  Targeted capture ctDNA Library CRCQV34Run002-6 from patient PBC0001627, plasma baseline sample

  Dataset EGAD00001010339

• Targeted capture ctDNA Library CRCQV34Run007-22

  Targeted capture ctDNA Library CRCQV34Run007-22 from patient PBC0002816, buffy coat sample

  Dataset EGAD00001010359

• Targeted capture ctDNA Library CRCQV42Run016-11

  Targeted capture ctDNA Library CRCQV42Run016-11 from patient PBC0001467, plasma baseline sample

  Dataset EGAD00001010399

• Targeted capture ctDNA Library CRCQV42Run021-13

  Targeted capture ctDNA Library CRCQV42Run021-13 from patient PBC0001299, plasma baseline sample

  Dataset EGAD00001010436

• Targeted capture ctDNA Library CRCQV42Run026-4

  Targeted capture ctDNA Library CRCQV42Run026-4 from patient PBC0002872, plasma baseline sample

  Dataset EGAD00001010496

• Targeted capture ctDNA Library CRCQV42Run029-23

  Targeted capture ctDNA Library CRCQV42Run029-23 from patient PBC0004350, plasma baseline sample

  Dataset EGAD00001010516

• Targeted capture ctDNA Library CRCQV42Run033-13

  Targeted capture ctDNA Library CRCQV42Run033-13 from patient PBC0002429, buffy coat sample

  Dataset EGAD00001010552

• Targeted capture ctDNA Library CRCQV42Run033-14

  Targeted capture ctDNA Library CRCQV42Run033-14 from patient PBC0002459, buffy coat sample

  Dataset EGAD00001010553

• Targeted capture ctDNA Library CRCQV42Run034-14

  Targeted capture ctDNA Library CRCQV42Run034-14 from patient PBC0004414, buffy coat sample

  Dataset EGAD00001010568

• Targeted capture ctDNA Library CRCQV42Run039-6

  Targeted capture ctDNA Library CRCQV42Run039-6 from patient PBC0002853, plasma baseline sample

  Dataset EGAD00001010622

• Targeted capture ctDNA Library CRCQV42Run039-8

  Targeted capture ctDNA Library CRCQV42Run039-8 from patient PBC0003334, plasma baseline sample

  Dataset EGAD00001010624

• Targeted capture ctDNA Library CRCQV42Run047-6

  Targeted capture ctDNA Library CRCQV42Run047-6 from patient PBC0001255, buffy coat sample

  Dataset EGAD00001010738

• Targeted capture ctDNA Library CRCQV42Run048-24

  Targeted capture ctDNA Library CRCQV42Run048-24 from patient PBC0005531, buffy coat sample

  Dataset EGAD00001010756

• Targeted capture ctDNA Library CRCQV42Run049-22

  Targeted capture ctDNA Library CRCQV42Run049-22 from patient PBC0002481, buffy coat sample

  Dataset EGAD00001010775

• Targeted capture ctDNA Library CRCQV42Run049-23

  Targeted capture ctDNA Library CRCQV42Run049-23 from patient PBC0001409, buffy coat sample

  Dataset EGAD00001010776

• Targeted capture ctDNA Library CRCQV42Run049-4

  Targeted capture ctDNA Library CRCQV42Run049-4 from patient PBC0004537, buffy coat sample

  Dataset EGAD00001010777

• Targeted capture ctDNA Library CRCQV42Run050-19

  Targeted capture ctDNA Library CRCQV42Run050-19 from patient PBC0001527, buffy coat sample

  Dataset EGAD00001010792

• Targeted capture ctDNA Library CRCQV42Run051-19

  Targeted capture ctDNA Library CRCQV42Run051-19 from patient PBC0002294, buffy coat sample

  Dataset EGAD00001010812

• SNF_RNAseq_CD138n_20f

  TPM matrices of counts from RNA sequencing (RNAseq) from baseline CD138(–) BM fractions.

  Dataset EGAD00001011142

• 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

• GenomeEUtwin Data Access Committee

  Access to data generated by the GenomeEUtwin is available by emailing application to the data access committee and will be granted to qualified investigators for appropriate use.

  Dac EGAC00000000007

• Dr. Fatima Mechta-Grigoriou, PhD, DR1 Head of Stress and Cancer Laboratory Deputy Director Genetic and Biology of Cancer Dpt Institut Curie - Inserm U830

  Dac EGAC00001000581

• 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

• EGAD00010000602

  WTCCC2 Reading and Mathematics ability (RM) samples from UK using the Affymetrix 6.0 array

  Dataset EGAD00010000602

• EGAD00010000270

  Metabric breast cancer samples (Images)

  Dataset EGAD00010000270

• Mutational Screening of Human Acute Myleloid Leukaemia Samples

  Mutational Screening of Human Acute Myleloid Leukaemia Samples

  Dataset EGAD00001000054

• Integrative Oncogenomics of Multiple Myeloma

  Integrative Oncogenomics of Multiple Myeloma

  Dataset EGAD00001000074

• Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing

  Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing

  Dataset EGAD00001000081

• UK10K_NEURO_MUIR REL-2012-01-13

  UK10K_NEURO_MUIR REL-2012-01-13

  Dataset EGAD00001000170

• Evaluation of PCR library method on whole genome samples

  Evaluation of PCR library method on whole genome samples

  Dataset EGAD00001000252

• Data set for Whole-genome-Sequencing of adult medulloblastoma

  Data set for Whole-genome-Sequencing of adult medulloblastoma

  Dataset EGAD00001000275

• ICGC prostate cancer whole genome sequencing

  ICGC prostate cancer whole genome sequencing

  Dataset EGAD00001000306

• UK10K_NEURO_MUIR REL-2012-11-27

  UK10K_NEURO_MUIR REL-2012-11-27

  Dataset EGAD00001000322

• Myeloproliferative Neoplasms (MPN) Exome Validation Study

  Experiments using targeted pulldown methods will be sequenced to validate findings in the exomes of patients with Myeloproliferative Neoplasms (MPN).

  Dataset EGAD00001000619

• Human Epidermis scRNA

  Single cell RNA-seq analysis of human skin.

  Dataset EGAD00010001620

• Imputed_genetics

  Imputed genetic data for INTERVAL proteomics cohort

  Dataset EGAD00010001544

• Normalised mRNA expressions

  Quantile-normalised and batch corrected

  Dataset EGAD00010001561

• Russian_TB_6.0

  Russian Tuberculosis samples using Affymetrix 6.0

  Dataset EGAD00010000901

• APP-G-1

  Array data from 4778 individuals from general population of rural Uganda

  Dataset EGAD00010000965

• BMI EWAS summary stats

  Summary statistics for a multi-cohort epigenome-wide association study. This includes summary statistics (effect-size, standard error, p-value) for 470,000 methylation markers.

  Dataset EGAD00010001029

• mtDNA-Roma

  mtDNA variant positions vcf files for 86 human samples

  Dataset EGAD00010001844