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• Melanoma_Til_Study_RNAseq

  In this study, mutations present in a series of human melanomas (stage IV disease) will be determined, using autologous blood cells to obtain a reference genome. From each of the samples that are analyzed, tumour-infiltrating T lymphocytes have also been isolated. This offers a unique opportunity to determine which (fraction of) mutations in human cancer leads to epitopes that are recognized by T cells. The resulting information is likely to be of value to understand how T cell activating drugs exert their action.

  Study EGAS00001000251

• Single cell sequencing of endoscopic biopsies from Barrett's oesophagus and proximal tissue from the normal GI tract

  Barrett’s oesophagus is a precursor of oesophageal adenocarcinoma. In this common condition, squamous epithelium in the oesophagus is replaced by columnar epithelium in response to acid reflux. Barrett’s oesophagus is highly heterogeneous and its relationships to normal tissues are unclear. We investigated the cellular complexity of Barrett’s oesophagus and the upper gastrointestinal tract using RNA-sequencing of single cells from multiple biopsies from six patients with Barrett’s oesophagus and two patients without oesophageal pathology.

  Study EGAS00001003144

• Amplicon_based_sequencing_of_drug_resistant_organoids

  A BRAF V600E colorectal organoid which is sensitive to MAP kinase inhibition was mutagenised with the chemical mutagen ENU and then drug selected using a combination of Trametinib, Dabrafenib and Cetuximab. Single cell derived organoids were then manually picked and expanded in drug. Resistance was confirmed in a 14 day assay and DNA was collected. These then underwent targeted amplicon-based sequencing to confirm candidate resistance effectors from a screen in 2 2D BRAF V600E colorectal cell lines. Pools of resistant clones were also sequenced.

  Study EGAS00001001639

• WES sequencing of malignant peripheral nerve sheath tumours

  Investigate the genomic landscape of MPNST tumours. Cases where a diagnosis of MPNST had been considered in the differential diagnosis with a variable degree of confidence was included. The diagnosis of MPNST was excluded in 12/51 (49 cases had WES data) of the sequenced tumours following review of the pathology, new IHC, molecular tests and clinical information. Article: Lyskjær et al, 2020, J Pathol, "H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours".

  Study EGAS00001004527

• We performed an integrative analysis to determine genomic aberrations common to sporadic schwannomas.

  Schwannomas are common peripheral nerve sheath tumors that can cause significant debilitating morbidities. We performed an integrative analysis to determine genomic aberrations common to sporadic schwannomas. Exome sequence analysis with validation by targeted DNA-sequencing of 125 samples uncovered, in addition to expected NF2 disruption additional recurrent mutations. RNA sequencing identified a recurrent in-frame SH3PXD2A-HTRA1 fusion in 12/125 (10%) cases, and genomic analysis demonstrated the mechanism as resulting from a balanced 19Mb chromosomal inversion on chromosome 10q.

  Study EGAS00001001886

• Discovering genetic causes of optic atrophy syndromes through whole exome sequencing

  The genetic defects leading to optic atrophy range from mitochondrial DNA (mtDNA) point mutations in Leber’s hereditary optic neuropathy (LHON), to dominant and recessive mutations affecting a cluster of nuclear genes implicated in mitochondrial dynamics. We performed WES in patients with an optic atrophy spectrum disorder, including retinal macular dystrophy and kidney insufficiency leading to transplantation, associated with mitochondrial DNA (mtDNA) depletion without accumulation of multiple deletions, to identify the genetic causes of this syndrome.

  Study EGAS00001003850

• Endothelium-derived stromal cells contribute to bone marrow niche formation

  Comprehensive transcriptional characterization of bone marrow stromal cells by RNA sequencing was performed to determine the molecular properties/signatures of endothelium during niche formation.Here, we identify a rare subset of cells in the human fetal BM that co-express endothelial and stromal markers, including low-affinity nerve growth factor receptor (LNGFR/CD271). They display transcriptional reprogramming consistent with endothelial-to-mesenchymal transition (EndoMT), reflected in their potential to generate stromal cells with in vivo BM niche forming capacity.

  Study EGAS00001004946

• Blood neutrophils in COPD derive from activated progenitors in the bone marrow

  Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small airway inflammation, emphysema and severe breathing difficulties. Low-grade systemic inflammation is an established hallmark of severe disease, however, the molecular changes in peripheral immune cells remain far from understood. We combined multi-color flow cytometry with single-cell RNA sequencing and showed that blood neutrophil numbers are significantly increased in COPD and they are a heterogeneous population. A transcriptomic state that expressed interferon response genes correlated with alveolar damage and acute exacerbations. Furthermore, bronchoalveolar neutrophils expressed gene signatures corresponding to certain blood neutrophil states. Last, our data in a murine model of cigarette smoke exposure demonstrated that bone marrow neutrophil progenitors are expanded in smoke-treated animals and display signs of immune activation. Our study provides evidence that COPD systemic inflammation may derive from an activated haematopoietic precursor compartment.

  Dataset EGAD00001008788

• Blood neutrophils in COPD derive from activated progenitors in the bone marrow sc Seqwell

  Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small airway inflammation, emphysema and severe breathing difficulties. Low-grade systemic inflammation is an established hallmark of severe disease, however, the molecular changes in peripheral immune cells remain far from understood. We combined multi-color flow cytometry with single-cell RNA sequencing and showed that blood neutrophil numbers are significantly increased in COPD and they are a heterogeneous population. A transcriptomic state that expressed interferon response genes correlated with alveolar damage and acute exacerbations. Furthermore, bronchoalveolar neutrophils expressed gene signatures corresponding to certain blood neutrophil states. Last, our data in a murine model of cigarette smoke exposure demonstrated that bone marrow neutrophil progenitors are expanded in smoke-treated animals and display signs of immune activation. Our study provides evidence that COPD systemic inflammation may derive from an activated haematopoietic precursor compartment.

  Dataset EGAD00001008908

• Blood neutrophils in COPD derive from activated progenitors in the bone marrow sc Rhapsody

  Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small airway inflammation, emphysema and severe breathing difficulties. Low-grade systemic inflammation is an established hallmark of severe disease, however, the molecular changes in peripheral immune cells remain far from understood. We combined multi-color flow cytometry with single-cell RNA sequencing and showed that blood neutrophil numbers are significantly increased in COPD and they are a heterogeneous population. A transcriptomic state that expressed interferon response genes correlated with alveolar damage and acute exacerbations. Furthermore, bronchoalveolar neutrophils expressed gene signatures corresponding to certain blood neutrophil states. Last, our data in a murine model of cigarette smoke exposure demonstrated that bone marrow neutrophil progenitors are expanded in smoke-treated animals and display signs of immune activation. Our study provides evidence that COPD systemic inflammation may derive from an activated haematopoietic precursor compartment.

  Dataset EGAD00001009704

• The genomic architecture of mesothelioma

  The genome-wide landscape of somatically acquired mutations in mesothelioma has not been deeply characterised to date, but advances in DNA sequencing technology now allow this to be addressed comprehensively. Harnessing massively parallel DNA sequencing platforms, we will identify somatically acquired point mutations in all coding regions of the genome from patients with mesothelioma. In addition, using paired-end sequencing, we will map copy number changes and genomic rearrangements from the same patients.

  Dataset EGAD00001000360

• ICARUS-LUNG01-RNAseq

  Bulk RNA-seq was carried out on 20 pairs of frozen tumor biopsies. Differential gene expression (DGE) analyses was conducted, looking at the fold change of gene expression of matched on-T/BL samples in the overall population and, then, separately in responders and non-responders.

  Study EGAS50000000732

• CRISPRi/a of GATA2/NR4A2/SOX17 upon spontaneous iPSC differentiation

  Arrayed CRISPR screens, modulating the expression of key lineage TFs GATA2 (mesoderm), SOX17 (endoderm), and NR4A2 (neuroectoderm) in hiPSCs via CRISPR interference or activation over a time-course of spontaneous differentiation (days cultured in vitro: 0, 4, 12, and 18).

  Study EGAS50000000819

• 3D chromatin contacts of iPSC (controls) and mDAN (differentiated neurons) cells

  Sequencing of 3 replicates per condition to gather insights on the 3D chromatin conformation of iPCS-derived neuronal progenitors (smNPCs) and mDANs using LowC. The downstream analysis studies changes in A and B compartment interactions and in topologically associated domains (TADs).

  Study EGAS50000001578

• HipSci_RNASEQ_Battens

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Battens patients.

  Study EGAS00001001987

• HipSci_RNASEQ_Ataxia

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from hereditary cerebral ataxia patients.

  Study EGAS00001001992

• HipSci_RNASEQ_BPD

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Blood platelet disorders patients.

  Study EGAS00001001993

• HipSci_RNASEQ_Hypertrophic_Cardiomyopathy

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Hypertrophic Cardiomyopathy patients.

  Study EGAS00001001994

• HipSci_RNASEQ_Congenital_hyperinsulinia

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Congenital hyperinsulinia patients.

  Study EGAS00001001988

• HipSci_RNASEQ_Macular_Dystrophy

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Macular Dystrophy patients

  Study EGAS00001001995

• HipSci_RNASEQ_Alport

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Alport syndrome patients.

  Study EGAS00001001986

• Multiple_Malignancy_Familial_Comparison

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

  Study EGAS00001000333

• HipSci_RNASEQ_Spastic_paraplegia

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Spastic paraplegia patients

  Study EGAS00001001991

• HipSci_RNASEQ_Kabuki

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from kabuki patients

  Study EGAS00001001989

• Whole exome sequencing of trio with primary immunodeficiency (IL2RB)

  A novel homozygous mutation in human IL2RB results in decreased IL-2RB protein expression and dysregulated IL-2/15 signaling. This hypomorphic mutation leads to decreased regulatory T cell frequency and abnormal NK cell compartment, with clinical manifestations of autoimmunity and susceptibility to CMV.

  Study EGAS00001003599

• HipSci_RNASEQ_Retinitis_Pigmentosa

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform RNAseq on iPS lines from Retinitis Pigmentosa patients

  Study EGAS00001001996

• Peruvian Genome Project - Whole Genome Sequencing

  In this study, we sequence 150 genomes to high coverage from Native American and mestizo populations in Peru. The majority of our samples possess greater than 90% Native American ancestry, which makes this the most extensive Native American sequencing project to date.

  Study EGAS00001004995

• Targeted sequencing about core genes involved in telomere biology in colorectal cancer patients

  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 (Life Technologies, Carlsbad, CA, USA).

  Study EGAS00001002977

• Whole-genome low pass sequencing of 3,514 Sardinian individuals

  The dataset includes the VCF files with the list of variants, and their frequency, found in 3,514 Sardinian individuals recruited from the SardiNIA longitudinal study (N=2090) and from a case-control study of autoimmune diseases in Sardinia (N=1424).

  Study EGAS00001002212

• Mexican Biobank Project

  In this study, we present the data from the Mexican Biobank Project: 50 WGS from individuals with Native American ancestry, and 6000 genotypes from samples from this project. This project highlights the necessity of better diversity representation in genomic databases is a scientific imperative.

  Study EGAS00001005797

• Clonality of circulating tumor cells in breast cancer brain metastases patients

  The incidence of brain metastases in breast cancer (BCBM) patients is increasing. These patients have a very poor prognosis and therefore identification of blood-based biomarkers, such as circulating tumor cells (CTCs) and understanding the genomic heterogeneity could help to personalize treatment options. In this study, DNA from individual CTCs as well as corresponding primary tumors and brain metastases were analyzed by next generation sequencing (NGS) in order to evaluate copy number aberrations and single nucleotide variations (SNVs).

  Dataset EGAD00001005020

• Ither NB in Organoids WGS dataset - Exploring high-throughput drug sensitivity testing in neuroblastoma cell lines and patient-derived tumor organoids in the era of precision medicine

  Ither NB in Organoids WGS dataset - We aimed to launch an online repository integrating genomics and transcriptomics with high-throughput drug screening (HTS) of nineteen commonly used neuroblastoma cell lines and fourteen generated neuroblastoma patient-derived organoids (NBL-PDOs) to improve identification of molecularly matched therapies and support clinical uptake.

  Dataset EGAD00001010282

• Whole exome sequencing in patients with ALS and concomitant FTD lacking the C9orf72 repeat expansion

  Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are part of a clinical, pathological and genetic continuum. The purpose of the present study was to assess the mutation burden that is present in ALS and/or FTD known disease-causing genes in 54 patients (16 with available postmortem neuropathological diagnosis) with concurrent ALS and FTD (ALS/FTD) not-carrying the C9orf72 hexanucleotide repeat expansion, the most important genetic cause in both diseases.

  Dataset EGAD00001003409

• Single-cell RNA-seq data of bronchoalveolar lavage (BAL) fluid in severe COVID-19 and SARS-CoV-2 stimulated classical blood monocytes

  We performed single-cell RNA-sequencing of cells in the bronchoalveolar lavage (BAL) fluid of severe COVID-19. In addition, we performed single-cell RNA-sequencing of SARS-CoV-2 stimulated classical blood monocytes. This study provides detailed insights into the alveolar macrophage response to SARS-CoV-2 infection and reveals a profibrotic macrophage response in severe COVID-19 patients.

  Dataset EGAD00001006827

• 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

• 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

• Whole exome sequencing of prDLBCL

  To investigate the mutational landscape of prDLBCL, 34 cases were selected for whole exome sequencing.

  Study EGAS50000000403

• 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