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• Normal sample for patient SA230

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA230

  Dataset EGAD00001009553

• Normal sample for patient SA231

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

  Dataset EGAD00001009554

• Normal sample for patient SA232

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA232

  Dataset EGAD00001009555

• Normal sample for patient SA233

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA233

  Dataset EGAD00001009556

• Normal sample for patient SA234

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

  Dataset EGAD00001009557

• Normal sample for patient SA237

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

  Dataset EGAD00001009558

• Normal sample for patient SA271

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA271

  Dataset EGAD00001009559

• Normal sample for patient SA277

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

  Dataset EGAD00001009560

• Normal sample for patient SA278

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA278

  Dataset EGAD00001009561

• Normal sample for patient SA997

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA997

  Dataset EGAD00001009573

• Normal sample for patient SA998

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA998

  Dataset EGAD00001009574

• Tumour sample for patient SA416

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA416

  Dataset EGAD00001009575

• Normal sample for patient SA597

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA597

  Dataset EGAD00001009572

• Normal sample for patient SA095

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA095

  Dataset EGAD00001009600

• Tumour sample for patient SA400

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA400

  Dataset EGAD00001009576

• Tumour sample for patient SA290

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA290

  Dataset EGAD00001009577

• Tumour sample for patient SA288

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA288

  Dataset EGAD00001009578

• Tumour sample for patient SA299

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA299

  Dataset EGAD00001009579

• Tumour sample for patient SA095

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA095

  Dataset EGAD00001009580

• Tumour sample for patient SA415

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA415

  Dataset EGAD00001009581

• Normal sample for patient SA718

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA718

  Dataset EGAD00001009582

• Normal sample for patient SA720

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

  Dataset EGAD00001009583

• Tumour sample for patient SA718

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA718

  Dataset EGAD00001009584

• Tumour sample for patient SA720

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

  Dataset EGAD00001009585

• Normal sample for patient SA1017

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009586

• Normal sample for patient SA1026

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

  Dataset EGAD00001009587

• Normal sample for patient SA1027

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1027

  Dataset EGAD00001009588

• Normal sample for patient SA1028

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

  Dataset EGAD00001009589

• Normal sample for patient SA1040

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1040

  Dataset EGAD00001009590

• Normal sample for patient SA1064

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1064

  Dataset EGAD00001009591

• Normal sample for patient SA1065

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1065

  Dataset EGAD00001009592

• Normal sample for patient SA1069

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1069

  Dataset EGAD00001009593

• Normal sample for patient SA1073

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009594

• Normal sample for patient SA1074

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1074

  Dataset EGAD00001009595

• Normal sample for patient SA576

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

  Dataset EGAD00001009596

• Normal sample for patient SA610

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009597

• Normal sample for patient SA992

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009598

• Normal sample for patient SA994

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

  Dataset EGAD00001009599

• Normal sample for patient SA288

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA288

  Dataset EGAD00001009601

• Normal sample for patient SA299

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA299

  Dataset EGAD00001009602

• Normal sample for patient SA415

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA415

  Dataset EGAD00001009603

• Normal sample for patient SA666

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA666

  Dataset EGAD00001009604

• Tumour sample for patient SA1065

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1065

  Dataset EGAD00001009605

• Tumour sample for patient SA1064

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1064

  Dataset EGAD00001009606

• Tumour sample for patient SA1026

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

  Dataset EGAD00001009607

• Tumour sample for patient SA1069

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1069

  Dataset EGAD00001009608

• Tumour sample for patient SA1017

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009609

• Tumour sample for patient SA1027

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1027

  Dataset EGAD00001009610

• Tumour sample for patient SA1073

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009611

• Tumour sample for patient SA1074

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1074

  Dataset EGAD00001009612

• Tumour sample for patient SA576

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

  Dataset EGAD00001009613

• Tumour sample for patient SA1028

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

  Dataset EGAD00001009614

• Tumour sample for patient SA1040

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1040

  Dataset EGAD00001009615

• Tumour sample for patient SA992

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009616

• Tumour sample for patient SA610

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009617

• Normal sample for patient SA416

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA416

  Dataset EGAD00001009618

• Normal sample for patient SA1070

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009619

• Tumour sample for patient SA1070

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009620

• Tumour sample for patient SA997

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA997

  Dataset EGAD00001009621

• Reconstruction of human terminal erythroid differentiation cell at single cell level

  Terminal erythroid differentiation cells(GYPA+ cells) were isolated from neonate cord blood(CB) and adult bowe marrow(BM). single cell transcriptome sequencing library was constructed by 10X genomics system and sequenced by Illumina X ten platform. Sequencing data was analyzed to profile dynamic expression genes and centre regulators during terminal erythroid differentiation stage within CB and BM.

  Study EGAS00001003114

• Single-nucleus RNA-sequencing of normal adrenal cortex and adrenocortical tumors

  This study reports a single-nucleus transcriptome atlas of steroid, stromal and immune cells in 38 human normal adrenals and adrenocortical tumors.

  Study EGAS50000000585

• ChIP Seq data of multiple myeloma and plasma cell leukaemia cell lines

  ChIP-seq data (H3K4Me1, H3K4Me3, H3K27Ac histone modifications) on multiple myeloma cell line KMS11 and plasma cell leukaemia cell lines L363 and JJN3

  Study EGAS00001002414

• Whole genome sequencing and somatic mutation profiles and whole genome transcription files of pediatric medulloblastoma

  Fastq, Mutect (SNVs), Platypus (indels), and InfoGenomeR (SVs and CNAs) calls from whole genome sequencing data and fastq files of whole genome transcription data of five patients with pediatric medulloblastoma.

  Dataset EGAD00001009507

• Single-cell profiling of co-cultures of GSCCs and macrophages

  This dataset contains scRNA-seq data from 8 co-cultures of GSCCs and macrophages, and 1 monoculture of macrophages. Samples were individually labeled and pooled using MULTI-seq technology and processed with 10x Genomics Technology.

  Dataset EGAD00001011275

• Androgen receptor blockade promotes response to BRAF/MEK-targeted therapy

  We studied a group of melanoma patients treated with neoadjuvant BRAF/MEK-targeted therapy (NCT02231775, n=51), and observed significantly higher rates of major pathologic response (MPR= <10% viable tumor at resection) and improved recurrence-free survival (RFS) in females versus males (MPR-66% versus 14%, p=0.001; RFS-64% versus 32% at 2 years, p=0.021). Findings were validated in a several additional cohorts 2-4 patients with unresectable metastatic melanoma treated with BRAF and/or MEK-targeted therapy (n=664 patients in total), demonstrating improved progression-free survival (PFS) and overall survival (OS) in females versus males in several of these studies. Studies in pre-clinical models demonstrated significantly impaired anti-tumor activity in male versus female BRAF/MEK-treated mice (p=0.006), with significantly higher expression of androgen receptor (AR) in tumors of male and female BRAF/MEK-treated mice versus control (p=0.0006 and 0.0025). Pharmacologic inhibition of AR signaling improved responses to BRAF/MEK-targeted therapy in male and female mice (p=0.018 and p=0.003), whereas induction of AR signaling (via testosterone administration) was associated with significantly impaired response to BRAF/MEK-targeted therapy in males and females (p=0.021 and p<0.0001).

  Study EGAS00001006196

• Mutational_signatures_and_clonal_dynamics_in_normal_human_tissues

  Somatic mutations (burdens and signatures) and clonal dynamics in normal human tissues

  Study EGAS00001002471

• HCA_Skin_Disease_Atopic_dermatitis_Wellcome_Spatial_Managed_Access

  Spatial transcriptomics of skin and PBMC samples from eczema patients, pre and post dupilumab treatment

  Study EGAS00001006482

• Massively Multiplex Single-Cell Hi-C of HeLa Cells

  In this study, we developed a massively multiplexed, single-cell Hi-C protocol to study the chromosomal architecture of single HeLa cells.

  Study phs001269

• Genome sequence comparison of human iPS cell lines

  We performed whole genome sequencing analysis on human iPSC lines to understand the impact of genetic variations on clonal epigenetic variations.

  Study JGAS000310

• Tumor mutational landscape in individuals with CMMRD

  Whole exome sequencing data from the tumors (n=16) of individuals with constitutional mismatch repair deficiency. Data was aligned to GRCh38.

  Study EGAS50000000081

• This data consists of iPSC derived model systems stimulated with different media.

  This data consists of iPSC derived model systems stimulated with different media (where possible from the top/bottom separately) to provide insight into which more accurately reflects the human gut environment.

  Dataset EGAD50000001918

• Peripheral blood DNA methylation data from CD patients prior to vedolizumab treatment from John Radcliffe Hospital

  DNA methylation validation data as obtained using the Illumina HumanMethylation EPIC BeadChip array (V1) on peripheral blood from CD patients at the John Radcliffe Hospital, Oxford, UK prior to vedolizumab treatment

  Dataset EGAD00010002652

• Peripheral blood DNA methylation data from CD patients prior to ustekinumab treatment from John Radcliffe Hospital

  DNA methylation validation data as obtained using the Illumina HumanMethylation EPIC BeadChip array (V1) on peripheral blood from CD patients at the John Radcliffe Hospital, Oxford, UK prior to ustekinumab treatment

  Dataset EGAD00010002650

• scRNAseq of T-cells from two responders to high-dose ipilimumab

  ScRNAseq of CD3 T-cells isolated from post-treatment bladder tissue from 2 samples from the NABUCCO 1 trial. Paired-end RNAsequencing was used on the Illumina NovaSeq 6000 sequencing platform.

  Dataset EGAD50000002557

• ImmunoAgeing_Colonies

  Using patterns of shared mutations between haematopoietic stem cells in 14 individuals with clonal haematpoiesis, we aim to determine the timing of somatic mutation acquisition.

  Study EGAS00001003933

• Exome_sequencing_of_Bilateral_Anophthalmia_cases__Pilot_Study_

  This pilot study aims to generate pilot data to inform future study designs by resequencing the whole exomes of 10 unrelated individuals diagnosed with Bilateral Anophthalmia.

  Study EGAS00001000356

• Lung_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Lung cancer through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing.

  Study EGAS00001000148

• Fungal infection in neural tissue from Amyotrophic Lateral Sclerosis

  The study shows that fungus infection, isolated from neural tissue, can be a risk factor to develop Amyothophic lateral sclerosis (ALS).

  Study EGAS00001002473

• SFHS_pedigrees

  Deep (>25x mean coverage) whole genome sequencing on 5-10 families drawn from the Scottish Family Health Study with four or more children.

  Study EGAS00001000078

• BS-seq in plasma of CRC patients

  We performed whole genome bisulfite sequencing of plasma DNA in 11 colorectal cancer patients to study the colonic DNA in plasma.

  Study EGAS00001003117

• Targeted sequencing about core genes implicated in telomere biology

  We sequenced the coding exons of core genes involved in telomere maintenance using peripheral blood DNA of 192 CRC patients. The primary sequencing data were generated by using Ion Torrent Personal Genome Machine® (PGM™) platform.

  Dataset EGAD00001004096

• Genotype data of Japanese

  Genotype data of the Japanese population (N=142) were collected at Osaka University. Genotyping was performed using Infinium Asian Screening Array (Illumina, USA).

  Study EGAS00001006950

• Sequencing of cell-free DNA from breast cancer patients

  To assess the utility of high coverage whole genome sequencing analysis of cell-free DNA to detect tumour-specific genomic changes

  Study EGAS00001004960

• Epigenome-wide association study of cocaine use disorder in postmortem human brain tissue

  We aimed to identify cocaine use disorder associated DNA methylation alterations in the Brodmann Area 9 brain region.

  Study EGAS00001006826

• Medulloblastoma-associated DDX3 variant selectively alters the translational response to stress

  Medulloblastoma-associated DDX3 variant selectively alters the translational response to stress

  Dataset EGAD00001001210

• H005 RNA-seq CLL

  Paired-end RNA sequencing using total RNA from 136 primary lymphoma samples. Sequencing was performed on the Illumina HiSeq2000 with 300bp insert size. The dataset contains FASTQ files.

  Dataset EGAD00001002056

• Detection of uniparental disomy in a family trio WGS

  We detected a uniparental paternal isodisomy event of chromosome 4 in a child. DNA was extracted from the blood. HiSeq X generated the sequence data.

  Dataset EGAD00001008676

• RNASeq

  The cohort comprised of 48 pediatric patients with 21 different relapsed or refractory solid neoplasms. This cohort was analysed by RNASeq. The corresponding datasets contains fasq files.

  Dataset EGAD00001010041

• Exploring_the_landscape_of_somatic_mutations_in_normal_tissue___POL___WGS

  Somatic mutations (burdens and signatures) and clonal dynamics in individuals with germline DNA polymerase mutations.

  Study EGAS00001003682

• Mycobacterium_Induced_Granuloma

  Spatial transcriptomics of human Mycobacterium granulomas reveals Spatial and Functional Architecture of Immune Response and Tissue Remodeling

  Study EGAS50000000998

• Co-infection of fungi and bacteria in brain tissue of Alzheimer’s patients.

  Metagenomics analysis reveals co-infection of fungi and bacteria isolated from different regions of brain tissue from elderly persons and patients with Alzheimer's disease.

  Study EGAS00001002766

• Exome and transcriptome sequencing of Desmoplastic Small Round Cell Sarcoma

  To conduct exome and transcriptome profiling to identify secondary recurrent mutations, multi-site phylogenetic analyse and immune characterization of Desmoplastic Small Round Cell Sarcoma.

  Study EGAS00001004575

• Gene_epression_regulation_in_cytokine_induced_immune_cell_states

  We isolated T cells and monocotyes from healthy platelet donors and cultured them in resting and stimulated conditions with addition of a range of cytokines. We performed RNA sequencing to assess impact of different disease-relevant cytokines upon immune cell responses.

  Study EGAS00001003823

• HLF COPD Transcriptomics

  We generated transcriptomes of primary human lung fibroblasts (HLFs) isolated from distal parenchyma of ex-smoker controls and COPD patients, with both mild and severe disease. RNA sequencing analysis demonstrated dysregulation of genes involved in proliferation, DNA repair, and extracellular matrix organization.

  Study EGAS00001006602

• Genomic and transcriptomic landscape of aggressive thyroid cancer

  Molecular characteristics of anaplastic thyroid cancer (ATC) and advanced differentiated thyroid cancers (DTCs) have not been fully elucidated. In this study, we applied various types of massively-parallel sequencing technology to 113 advanced TCs, including 27 ATCs and 86 advanced DTCs, to reveal their genomic and transcriptomic characteristics.

  Study EGAS00001003540

• Evaluation of capture and amplicon-based targeted sequencing methods on formalin-fixed tumours

  Evaluated performance of three capture (Agilent’s SureSelectXT HS, Illumina’s Nextera Rapid Capture Custom, and New England Biolabs’ Next Direct Custom) and one amplicon-based (Qiagen’s Human Breast Cancer Panel) targeted sequencing methods on paired blood and FFPE, using whole exome sequencing data from matched fresh-frozen tissue as a comparison.

  Study EGAS00001004965

• Novel Gene-Environment Regulatory Circuit in Chamber-Specific Growth of Perinatal Heart

  We report a case of hypertrophic cardiomyopathy and lactic acidosis in a 3-year-old female. Cardiac and skeletal muscle biopsies exhibited mitochondrial hyperplasia with decreased complex VI activity. Whole exome sequencing identified compound heterozygous variants, p.Arg333Trp and p.Val119Leu, in TSFM, a nuclear gene that encodes a mitochondrial translation elongation factor, resulting in impaired oxidative phosphorylation and juvenile hypertrophic cardiomyopathy.

  Study phs002725

• A Phase II Study: CRS207/GVAX Plus Anti-PD1 and Anti-CTLA4 Recruits Mesothelin- and KRAS-Specific T cells into PDAC

  This study examined immunologic correlatives from a phase II study evaluating CRS207/GVAX vaccines in combination with anti-PD1 and anti-CTLA4 in metastatic pancreatic cancer (NCT03190265). Arm A received CRS207/GVAX with anti-PD1 and anti-CTLA4 therapy; Arm B received CRS207 with anti-PD1 and anti-CTLA4 therapy. Patients undergoing treatment in this trial had peripheral blood mononuclear cells (PBMCs) and tumor tissue biopsied serially at pre-treatment and on-treatment timepoints. Single-cell RNA/TCR sequencing was employed on PBMCs. Bulk RNA/TCR sequencing was employed on tumor tissues. We identified treatment-enriched inflammatory pathways as well as T cell repertoires.

  Study phs003798

• NOTCH1 orchestrates metabolic reprogramming to drive proliferation in chronic lymphocytic leukemia

  In Chronic lymphocytic leukemia (CLL), NOTCH1 mutations occur in ~10% of cases and are often associated with unmutated IGHV genes, defining a subgroup requiring earlier treatment. Using an engineered CLL cell line, we demonstrated that NOTCH1-mutated cells exhibit increased glucose uptake, oxidative metabolism, and proliferation, driven by enhanced mitochondrial mass and TFAM upregulation. Metabolic assays and stable isotope tracing revealed a greater dependency on glutamine and anabolic pathways in NOTCH1-mutated cells, promoting growth. These findings were validated in a cohort of NOTCH1-mutated patients, highlighting a molecular circuit linking BCR, NOTCH1, and mitochondrial metabolism. This study suggests that metabolic vulnerabilities in NOTCH1-mutated CLL could inform precision medicine strategies.

  Study EGAS50000000981

• Whole genome sequencing analysis of hepatoblastoma

  Whole genome sequencing analysis of pediatiric liver tumor, hepatoblastoma, and their genomic and epigenomic features.

  Study JGAS000156