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• McGill EMC Release 4 in tissue "venous blood" for cell type "Monocyte"

  McGill EMC Release 4 in tissue "venous blood" for cell type "Monocyte"

  Dataset EGAD00001001282

• McGill EMC Release 4 in tissue "venous blood" for cell type "eosinophil"

  McGill EMC Release 4 in tissue "venous blood" for cell type "eosinophil"

  Dataset EGAD00001001281

• Maternal Plasma RNA Sequencing for Genomewide Transcriptomic Profiling and Identification of Pregnancy-Associated Transcripts

  Maternal Plasma RNA Sequencing for Genomewide Transcriptomic Profiling and Identification of Pregnancy-Associated Transcripts

  Dataset EGAD00001001609

• WXS files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  WXS files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  Dataset EGAD00001015801

• 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

• WGS files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  WGS files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  Dataset EGAD00001015800

• RNASeq files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  RNASeq files for paper titled "Patient-derived pediatric brain tumor organoids faithfully recapitulate primary tumors"

  Dataset EGAD00001015802

• Remaining WGS files for Klco RPAML data

  Remaining WGS files for study titled "Genomics of pediatric myeloid neoplasms"

  Dataset EGAD00001008446

• Clinical significance of novel subtypes of acute lymphoblastic leukemia in the context of minimal residual disease-directed therapy

  We evaluate clinical significance of recently identified subtypes of acute lymphoblastic leukemia (ALL) in 598 children treated with minimal residual disease (MRD)-directed therapy. Among the 16 B-ALL and 8 T-ALL subtypes identified by next generation sequencing, ETV6-RUNX1, high-hyperdiploid and DUX4-rearranged B-ALL had the best five-year event-free survival rates (95% to 98.4%); TCF3-PBX1, PAX5alt, T-cell, ETP, iAMP21, and hypodiploid ALL intermediate rates (80.0% to 88.2%); and BCR-ABL1, BCR-ABL1-like and ETV6-RUNX1-like and KMT2A-rearranged ALL the worst rates (64.1% to 76.2%). All but three of the 142 patients with day-8 blood MRD <0.01% remained in remission. Among new subtypes, intensified therapy based on day-15 MRD≥1% improved outcome of DUX4-rearranged, BCR-ABL1-like, and ZNF384-rearranged ALL, and achievement of day-42 MRD<0.01% did not preclude relapse of PAX5alt, MEF2D-rearranged and ETV6-RUNX1-like ALL. Thus, new subtypes including DUX4-rearranged, PAX5alt, BCR-ABL1-like, ETV6-RUNX1-like, MEF2D-rearranged and ZNF384-rearranged ALL have important prognostic and therapeutic implications.

  Study EGAS00001005084

• The Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project: Defining a Healthy Volunteer Cohort

  The integration of comprehensive genomic and phenotypic data from diverse ethnic populations offers unprecedented opportunities towards advancements in precision medicine and novel diagnostic technologies. Current reference genomic databases are not representative of the global human population, making variant interpretation challenging, especially in underrepresented populations such as the North African population. To address this, the Egyptian Collaborative Cardiac Genomics (ECCO-GEN) Project launched a study comprising 1000 individuals free of cardiovascular disease (CVD). Here, we present the first 391 Egyptian healthy volunteers (EHVols) recruited to establish a pilot phenotyped control cohort. All individuals underwent detailed clinical investigation, including cardiac MRI, and were sequenced using a targeted panel of 174 genes with reported roles in inherited cardiac conditions (ICC). We identified 1,262 variants in 27 cardiomyopathy genes of which 15.1% were not captured in current global and regional genetic reference databases (here: gnomAD and Great Middle Eastern (GME) Variome). The ECCO-GEN project aims at defining the genetic landscape of an understudied population and providing individual-level genetic and phenotypic data to support future studies in CVD and population genetics.

  Study EGAS00001004434

• Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures

  Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genome- wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. Autosome-defined clusters were characterized by cluster-specific AR gene architectures that in two index cases were topologically more congruent than by chance (p-values 0.03, 3.07x10-8). Integration with anatomical site suggested patterns of spread and points of genomic divergence. Copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories.

  Study EGAS00001006598

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

  Study EGAS00001004502

• SMARCA4/2 loss inhibits chemotherapy-induced apoptosis by restricting IP3R3-mediated Ca2+ flux to mitochondria

  Study EGAS00001005448

• Baseline RNAseq analysis of POETIC Good/Poor Responders to aromatase inhibitors based on change in Ki67

  Study EGAS00001007302

• HCC.GNE RNA-Seq

  RNA-Sequencing data (raw read sequences) for 23 samples, from 12 patients, for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma"

  Dataset EGAD00001000886

• CCA methylation data (12 CCA, 7 normal)

  Raw idat files for DNA methylation profiling for 12 CCAs and 7 normal bile duct tissues. DNA methylation profiling was performed using Infinium MethylationEPIC v2.0 Kit.

  Dataset EGAD00010002613

• RNA-seq data for Heterogeneity of IKZF1 genomic alterations and risk of relapse in childhood BALL

  RNA-seq data for 14 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000151

• Single-cell RNA-seq of Bone marrow samples

  For two donors, we collected CD34 plus and CD34 minus hematopoietic cells for the single-cell RNA-seq analysis.

  Dataset EGAD50000000514

• sc-DECISION

  Data derived from PBMC and blood samples for the single cell and bulk RNAseq analysis for the sc-DECISION paper. https://doi.org/10.1101/2025.02.04.25321370

  Dataset EGAD50000001622

• HeLa S3 (CCL-2.2) HiC Sequencing

  HiC chromatin conformation sequencing was performed for the purpose of chromosome fusion and structural rearrangement identification.

  Study phs000665

• Liver Regulatory Genomics Data Access Committee

  Data access committee for genomic datasets generated for human liver tissue and human primary liver cells by the Regulatory Genomics of Metabolic Disease group (Imperial College London, Section of Genetics and Genomics).

  Dac EGAC50000000715

• single cell transcriptomic analysis of tumor samples collected from 5 patients with EMM

  Contains the raw single cell RNAseq data used for the study

  Study EGAS50000000034

• Normal sample for patient SA224

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA224

  Dataset EGAD00001009548

• Tumour sample for patient SA720

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009585

• Exome and Transcriptome for gynecologic cancer gene-drug analysis

  Total of 180 gynecologic tumor specimens were subjected for targeted-exome and/or whole-transcriptome sequencing.

  Dataset EGAD00001005331

• Tumour sample for patient SA588

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA588

  Dataset EGAD00001009194

• Tumour sample for patient SA601

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA601

  Dataset EGAD00001009205

• Tumour sample for patient SA590

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA590

  Dataset EGAD00001009196

• Tumour sample for patient SA654

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA654

  Dataset EGAD00001009206

• Normal sample for patient SA604

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA604

  Dataset EGAD00001009217

• Normal sample for patient SA398

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA398

  Dataset EGAD00001009231

• Normal sample for patient SA221

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA221

  Dataset EGAD00001009362

• Tumour sample for patient SA425

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA425

  Dataset EGAD00001009356

• Tumour sample for patient SA234

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA234

  Dataset EGAD00001009525

• Tumour sample for patient SA226

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA226

  Dataset EGAD00001009532

• Tumour sample for patient SA231

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA231

  Dataset EGAD00001009535

• Normal sample for patient SA591

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA591

  Dataset EGAD00001009241

• Exome and Transcriptome for gastric cancer gene-drug analysis

  Newly generated 52 gastric tumor specimens were subjected for targeted-exome and/or whole-transcriptome sequencing

  Dataset EGAD00001005766

• Tumour sample for patient SA591

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA591

  Dataset EGAD00001009197

• TENX066

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX066 1 samples; filetype=fastq

  Dataset EGAD00001006481

• SCRNA10X_SA_CHIP0149_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0149_001 1 samples; filetype=fastq

  Dataset EGAD00001006467

• SCRNA10X_SA_CHIP0080_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0080_001 1 samples; filetype=fastq

  Dataset EGAD00001006461

• SCRNA10X_SA_CHIP0142_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0142_001 1 samples; filetype=fastq

  Dataset EGAD00001006464

• SCRNA10X_SA_CHIP0142_003

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0142_003 1 samples; filetype=fastq

  Dataset EGAD00001006465

• SCRNA10X_SA_CHIP0146_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0146_002 1 samples; filetype=fastq

  Dataset EGAD00001006466

• SCRNA10X_SA_CHIP0149_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0149_002 1 samples; filetype=fastq

  Dataset EGAD00001006468

• SCRNA10X_SA_CHIP0150_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0150_002 1 samples; filetype=fastq

  Dataset EGAD00001006470

• SCRNA10X_SA_CHIP0152_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0152_001 1 samples; filetype=fastq

  Dataset EGAD00001006471

• SCRNA10X_SA_CHIP0163_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0163_002 1 samples; filetype=fastq

  Dataset EGAD00001006474

• TENX064

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX064 1 samples; filetype=fastq

  Dataset EGAD00001006479

• RNA data for Glioblastoma (EGAS00001003953, H016)

  RNA data for human glioblastoma patients, EGAS00001003953. 64 human samples, 2 cell lines (LN229, ZH487).

  Dataset EGAD00001006547

• SCRNA10X_SA_CHIP0080_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0080_002 1 samples; filetype=fastq

  Dataset EGAD00001006462

• SCRNA10X_SA_CHIP0163_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0163_001 1 samples; filetype=fastq

  Dataset EGAD00001006473

• SCRNA10X_SA_CHIP0063_000

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0063_000 1 samples; filetype=fastq

  Dataset EGAD00001006478

• SCRNA10X_SA_CHIP0152_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0152_002 1 samples; filetype=fastq

  Dataset EGAD00001006472

• SCRNA10X_SA_CHIP0172_001

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0172_001 1 samples; filetype=fastq

  Dataset EGAD00001006475

• TENX062

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX062 1 samples; filetype=fastq

  Dataset EGAD00001006477

• TENX065

  Transcriptome profiling by high-throughput sequencing for single cells for library TENX065 1 samples; filetype=fastq

  Dataset EGAD00001006480

• Tumour sample for patient SA676

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA676

  Dataset EGAD00001009343

• Tumour sample for patient SA1028

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1028

  Dataset EGAD00001009614

• Tumour sample for patient SA600

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA600

  Dataset EGAD00001009204

• SCRNA10X_SA_CHIP0172_002

  Transcriptome profiling by high-throughput sequencing for single cells for library SCRNA10X_SA_CHIP0172_002 1 samples; filetype=fastq

  Dataset EGAD00001006476

• Normal sample for patient SA495

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA495

  Dataset EGAD00001009372

• Tumour sample for patient SA668

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA668

  Dataset EGAD00001009211

• DATA FILES FOR MULLIGHAN MEF2D RNASEQ STRANDED

  DATA FILES FOR MULLIGHAN MEF2D RNASEQ STRANDED

  Dataset EGAD00001002692

• Normal sample for patient SA1026

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1026

  Dataset EGAD00001009587

• Tumour sample for patient SA101

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA101

  Dataset EGAD00001009527

• Tumour sample for patient SA277

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA277

  Dataset EGAD00001009539

• Normal sample for patient SA237

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA237

  Dataset EGAD00001009558

• Normal sample for patient SA576

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA576

  Dataset EGAD00001009596

• Normal sample for patient SA530

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA530

  Dataset EGAD00001009234

• Tumour sample for patient SA276

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA276

  Dataset EGAD00001009182

• Tumour sample for patient SA655

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA655

  Dataset EGAD00001009207

• Normal sample for patient SA402

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA402

  Dataset EGAD00001009232

• Tumour sample for patient SA592

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA592

  Dataset EGAD00001009198

• Tumour sample for patient SA595

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA595

  Dataset EGAD00001009200

• Tumour sample for patient SA599

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA599

  Dataset EGAD00001009203

• Tumour sample for patient SA283

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA283

  Dataset EGAD00001009184

• Normal sample for patient SA665

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA665

  Dataset EGAD00001009252

• Normal sample for patient SA404

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA404

  Dataset EGAD00001009233

• Normal sample for patient SA535

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA535

  Dataset EGAD00001009235

• Tumour sample for patient SA279

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA279

  Dataset EGAD00001009183

• Tumour sample for patient SA398

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA398

  Dataset EGAD00001009188

• Tumour sample for patient SA593

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA593

  Dataset EGAD00001009199

• Normal sample for patient SA605

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA605

  Dataset EGAD00001009218

• Normal sample for patient SA609

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA609

  Dataset EGAD00001009219

• Normal sample for patient SA595

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA595

  Dataset EGAD00001009244

• Normal sample for patient SA599

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA599

  Dataset EGAD00001009247

• Normal sample for patient SA655

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA655

  Dataset EGAD00001009251

• Normal sample for patient SA671

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA671

  Dataset EGAD00001009256

• Tumour sample for patient SA609

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA609

  Dataset EGAD00001009262

• Tumour sample for patient SA994

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA994

  Dataset EGAD00001009259

• Tumour sample for patient SA605

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA605

  Dataset EGAD00001009261

• Normal sample for patient SA669

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA669

  Dataset EGAD00001009255

• Tumour sample for patient SA674

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA674

  Dataset EGAD00001009341

• Tumour sample for patient SA673

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA673

  Dataset EGAD00001009340

• Tumour sample for patient SA675

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA675

  Dataset EGAD00001009342

• Tumour sample for patient SA677

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA677

  Dataset EGAD00001009344

• Tumour sample for patient SA678

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA678

  Dataset EGAD00001009345

• Tumour sample for patient SA679

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA679

  Dataset EGAD00001009346