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• Clonal dynamics of normal hepatocyte expansions in homeostatic human livers and their association with the biliary epithelium

  BAM files containing paired-end mtDNA sequencing data from morphologically normal human liver. CCO-proficient hepatocytes acquired from livers in which clonal CCO-deficient hepatocyte patches had been previously identified. Individual BAM files are named according to their patch, line and sample location, where PT denotes tissue near to the portal triad (PT), central hepatic vein (CV) and midway between these two structures (Mid). "Stroma" control samples were used for identifying germ-line variants. Sequenced on NextSeq 500 platform.

  Study EGAS00001006962

• This study aims to evaluate the relationship between cardiometabolic risk factors and the most common genetic variation (SNPs)

  Comprehensive data on lifestyle-related modifiable factors, sociodemographic, anthropometric, economic, biochemical, and genetic markers related to the occurrence of cardiometabolic diseases as part of the observational cross-sectional survey “2015 Health Survey of Sao Paulo with Focus on Nutrition (2015 ISA-Nutrition)”, a population-based study. Data of 805218 SNPs for 841 individuals was genotyped using the Axiom™ 2.0 Precision Medicine Research Array in the Thermo Fisher Scientific laboratory (Affymetrix Inc, Santa Clara, CA).

  Study EGAS00001007818

• RNA data for medulloblastoma samples (ICGC)

  RNA sequencing data for 170 medulloblastoma tumor samples

  Dataset EGAD00001003279

• Genetics of gene expression in human macrophage response to Salmonella

  Understanding how cells sense and respond to their environment, and how these responses are modulated by genetic variation, are fundamental biological problems, particularly for understanding how pathogenic organisms invade and manipulate the cells of the human immune system. Macrophages recognize and respond to many important human pathogens including HIV-1, Mycobacteria tuberculosis and Salmonella. This study will focus on the cellular response of human macrophages to Salmonella infection and how this response is modulated by the genetic bacground of the individual as well as additional pro-inflammatory stimulus (interferon-gamma priming). We will acquire 100 human induced pluripotent stem cell lines from the HipSci project, differentiate the cells in vitro into macrophages and expose them to four environmental conditions: (i) no stimulation, (ii) interferon-gamma (18h), (iii) Salmonella typhimurium SL1344 (5h), (iv) interferon-gamma (18h) + Salmonella (5h).Subsequently, we will isolate RNA from the samples for sequencing.

  Dataset EGAD00001003204

• Anaplastic Meningioma WGS-X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Dataset EGAD00001001267

• SPECTA: NGS Screening Program for Efficient Clinical Trial Access

  SPECTA comprises a network of participating European clinical sites and NGS screening platforms that can screen individual patients for multiple molecular targets and potentially allow the design of trials that will match the specific biology of the diseases affecting specific patients with cancer.

  Dataset EGAD00001000894

• Autozygosity pilot - British-Pakistani from Birmingham

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 50-80%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing British-Pakistani cohort samples from Birmingham will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consist of low coverage whole exome sequencing on these samples.

  Dataset EGAD00001001025

• Autozygosity pilot - British-Pakistani from Birmingham 2

  The offspring of first cousin marriages have ~6% of their genome autozygous, i.e. homozygous identical by descent, or even more if there was further consanguinity in their ancestry. In the UK there are large populations with very high first cousin marriage rates of 20-50%. Sequencing the exomes of a sample of these individuals has the potential both to support genetic health programmes in these populations, and to provide genetic research information about rare loss of function mutations. This pilot study based on existing British-Pakistani cohort samples from Birmingham will identify homozygous individuals for almost all variants down to an allele frequency around 1%, plus individuals carrying hundreds of new homozygous rare loss-of-function variants, and will support development of community relations and ethics for a wider study currently being designed. The data deposited in the EGA consists of low coverage whole exome sequencing on these samples.

  Dataset EGAD00001001026

• Targeted bisulfite sequencing

  Raw reads from targeted bisulfite sequencing. The SureSelect Methyl-Seq target enrichment system (Agilent Technologies, Inc., CA, USA) was used to prepare bisulfite sequencing libraries from blood DNA samples of lymphoma patients (Ly1, Ly2), healthy family members (Ly8, Ly9, Ly10, Ly11, Ly12, Ly13 and Ly14), baseline controls (Control1-5), DNMT3A mutation carriers (Id5, Id7, Id9, Id11) and their age-matched controls (Id6, Id8, Id10, Id12). In addition, blood DNA sample of a patient (HLRCC_N7) with germline fumarate hydratase (FH) mutation is included. Illumina paired-end sequencing for targeted libraries from Ly1, Ly2, Ly8, Ly9, Ly10 and Ly11 was done at Karolinska Institutet using 100 base-pair read length and the HiSeq2000 platform. Illumina paired-end sequencing for targeted libraries from Ly12, Ly13, Ly14, and DNMT3A mutation carriers and their age-matched controls was done as a service at BGI (BGI Tech Solutions Co., Ltd., China) using 126 base-pair read length and the HiSeq2500 platform.

  Dataset EGAD00001004785

• Massive parallel RNA sequencing of highly purified mesenchymal cells derived from bone marrow specimens of 45 low-risk myelodysplastic syndrome cases

  Highly purified mesenchymal cells (CD45-/7AAD-/CD235a-/CD31-/CD271+/CD105+) were prospectively FACS-isolated from bone marrow specimens of 45 low-risk myelodysplastic syndrome (LRMDS) cases. Gene expression profiles (GEPs) of the 45 LRMDS have been compared to GEPs derived from likewise highly purified mesenchymal cells obtained from bone marrow specimens of healthy donors for the identification of inflammatory signatures. Additionally, an overlap in inflammatory signatures has been determined by comparing the GEPs of these 45 LRMDS cases to the GEPs of 4 Shwachman-Diamond syndrome and 3 Diamond-Blackfan anemia cases, both representing different subclasses of congenital pre-leukemia syndromes with a tendency of leukemic progression and perturbed niche compartment. Finally, the GEPs and gene expression signatures have been utilized for prognostication and the prediction of leukemic progression.

  Dataset EGAD00001002658

• Patient tumour data (RNAseq, WGBS, ChIPseq, WGS)

  Content: 60 GB patient tumours and 4 normal brain samples combined in pairs by region (x2=8 total input samples). RNAseq: 1 lane per sample, total strand-specific rRNA-depleted (normal samples were combined = 2 lanes/samples per brain region). WGBS: 2 lanes per sample (normal samples were combined = 2 lanes/samples per brain region). ChIPseq (histone mark): a subset of 20 GB samples were profiled. For the same modification were multiplexed and sequenced on 4 lanes each (H3K27ac, H3K4me1) or a single lane (all others). WGS: used as matching input control for the 20 ChIPseq samples. Data type and technology: RNA-seq: PE 100bp sequenced on HiSeq2000. WGBS: PE 100bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000. WGS: PE 150bp sequenced on HiSeq X.

  Dataset EGAD00001005492

• Profiling molecular heterogeneity in human primary microglia

  In the brain the cells that control inflammation are called a type of white blood cell called microglia. Microglia are located throughout the brain and spinal cord and account for 10–15% of all cells found within the brain. As the resident white blood cells, they are the main active immune defence in the central nervous system (CNS). Microglia are part of an important class of cells known as macrophages that have two main states: M1 and M2. M1 cells are pro- inflammatory, leading to more inflammation, while M2 are anti-inflammatory, and drive wound healing. In this study, we will collect primary microglia from surgical biospies of 100 individuals. 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/

  Dataset EGAD00001005736

• RNA-sequencing of meningiomas for integrative molecular classification.

  RNA-sequencing of meningiomas for integrative molecular classification.

  Dataset EGAD00001007494

• RNA-Seq dataset for Genomic rearrangements in Pediatric Cancer

  RNA-Seq data for systematic gene fusion detection in Pediatric Cancer

  Dataset EGAD00001008152

• COVID-19 Severity First Wave of Infection for Severe Patients in Madrid

  We recruited 98 hospitalised patients displaying severe COVID-19 symptoms from the first wave of infection. A stringent exclusion criteria based on non-genetic factors such as age, blood oxygen, radiologic findings and other typical COVID-19 signs was performed. Gingival or peripheral blood samples were taken for 98 individuals and whole exome sequencing performed using ExomeCapture-Seq capture KAPA HyperExome on Illumina machines.

  Dataset EGAD00001008464

• Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis

  Nasal epithelial cells of PCD and non-PCD patients grown at air-liquid interface for RNAseq analysis. A total of 10 non-PCD patients (ALI day 14), 9 non-PCD patients (ALI day 21), 8 non-PCD patients (ALI day 28), 4 PCD patients (ALI day 14, day 21 and day 28), and 23 PCD patients (ALI day 21). Non-PCD patients and the 4 PCD patients on the three ALI days were sequenced at a depth of 100M reads, the remaining 23 PCD patients were sequenced at a depth of 70M. Overall sequencing design was rRNA depletion and 150bp paired-end.

  Dataset EGAD00001009498

• Tumour sample for patient SA287

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA287

  Dataset EGAD00001009185

• Tumour sample for patient SA588

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

  Dataset EGAD00001009194

• Tumour sample for patient SA586

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA586

  Dataset EGAD00001009193

• Tumour sample for patient SA585

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA585

  Dataset EGAD00001009192

• Tumour sample for patient SA530

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

  Dataset EGAD00001009191

• Tumour sample for patient SA404

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

  Dataset EGAD00001009190

• Tumour sample for patient SA402

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

  Dataset EGAD00001009189

• Tumour sample for patient SA398

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

  Dataset EGAD00001009188

• Tumour sample for patient SA395

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA395

  Dataset EGAD00001009187

• Tumour sample for patient SA394

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA394

  Dataset EGAD00001009186

• Tumour sample for patient SA283

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

  Dataset EGAD00001009184

• Tumour sample for patient SA279

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

  Dataset EGAD00001009183

• Tumour sample for patient SA276

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

  Dataset EGAD00001009182

• Tumour sample for patient SA275

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA275

  Dataset EGAD00001009181

• Tumour sample for patient SA274

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA274

  Dataset EGAD00001009180

• Tumour sample for patient SA272

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA272

  Dataset EGAD00001009179

• Tumour sample for patient SA219

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA219

  Dataset EGAD00001009178

• Tumour sample for patient SA218

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA218

  Dataset EGAD00001009177

• Single Cell Genome Sequence for DLP+ library A95618B

  Single Cell Genome Sequence for Triple negative breast cancer patient-derived xenograft SA609 passage 3 on DLP+ library A95618B

  Dataset EGAD00001009316

• Single Cell Genome Sequence for DLP+ library A95629B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051D passage 1 on DLP+ library A95629B

  Dataset EGAD00001009320

• Single Cell Genome Sequence for DLP+ library A95632A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA1-/- Tp53-/- cell line 184-hTERT-22 L9 83.86 on DLP+ library A95632A

  Dataset EGAD00001009321

• Single Cell Genome Sequence for DLP+ library A95634A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1091A passage 1 on DLP+ library A95634A

  Dataset EGAD00001009323

• Single Cell Genome Sequence for DLP+ library A95635A

  Single Cell Genome Sequence for immortalized breast epithelium - BRCA2-/-; Tp53-/- cell line 184-hTERT-22 L9 116.126 on DLP+ library A95635A

  Dataset EGAD00001009324

• Single Cell Genome Sequence for DLP+ library A95650A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052J passage 1 on DLP+ library A95650A

  Dataset EGAD00001009325

• Single Cell Genome Sequence for DLP+ library A95652A

  Single Cell Genome Sequence for immortalized breast epithelium BRCA2+/- Tp53-/- cell line 184-hTert L9 116.66 on DLP+ library A95652A

  Dataset EGAD00001009326

• 10x Genomics Single Cell Gene Expression for SA1096A

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient SA1096

  Dataset EGAD00001009139

• Spatial transcriptome sequence data from cross section of cancer containing prostates

  Spatial transcriptome sequence data from two tumour containing prostates. Entire cross section of organ divided into cubes to fit spatial transcriptomics arrays. The dataset contains paired-end sequences from 21 sections of 1k array sections and 9 sections of 10x Visium sections for patient 1 as well as 28 sections of 10x Visium sections for patient 2.

  Dataset EGAD00001008644

• Mucosal 16S sequencing data

  16S-V4 rRNA gene sequence data for intestinal biopsies from NCT02749630 trial participants. Biopsies from patients were collected at screening, day 30, and day 85 and prepared for 16SV4 rRNA gene sequencing.

  Dataset EGAD00001008843

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• CCA RNA-seq data (60 CCA, 6 normal, 16 cell-line)

  Fastq files for RNA-seq for 60 CCAs, 6 normal bile duct tissues, 14 CCA cell-lines (including replicates), and 2 normal cholangiocyte cell-lines (including replicates). RNA was extracted using the Qiagen RNeasy Mini kit. Illumina Tru-Seq Stranded Total RNA kit (Illumina, San Diego, California, USA) was used to prepare RNA libraries from 1 µg of total RNA. Paired-end 150 bp sequencing was performed using Illumina HiSeq4000 sequencer with the paired-end 150 bp read option.

  Dataset EGAD00001011998

• NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

  T-cell lymphoblastic lymphoma (T-LBL) is a common pediatric malignancy accounting for approximately 20% of the non-Hodgkin lymphomas during childhood. Survival rates of T-LBL are ~80%, but outcome after relapse is dismal, with salvage rates reaching only ~15. Considering the extremely poor prognosis after relapse and absence of clinically relevant high-risk genetics, there is an urgent need for the identification of molecular risk factors and new prognostic biomarkers in T-LBL, as well as identification of new therapeutic strategies. In this study we present a novel entity of high-risk pediatric T-LBL patients characterized by previously unknown NOTCH1 gene fusions and highly elevated blood TARC levels

  Dataset EGAD00001015255

• WES data for Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma

  Neuroblastoma (NB) is one of the most lethal childhood cancers due its propensity to treatment resistance. By spatial mapping of subclone geographies before and after chemotherapy across 89 tumor regions from 12 NBs, we find that densely packed territories of closely related subclones present at diagnosis are replaced under effective treatment by islands of distantly related survivor subclones, originating from a different most recent ancestor compared to lineages dominating before treatment. Conversely, in tumors that progressed under treatment, ancestors of subclones dominating later in disease are present already at diagnosis. Chemotherapy treated xenografts and cell culture models replicates these two contrasting scenarios and shows branching evolution to be a constant feature of proliferating NB cells. Phylogenies based on whole genome sequencing of 505 individual NB cells indicate that a rich repertoire of parallel subclones, emerges already with the first oncogenic mutations and lays the foundation for clonal replacement under treatment.

  Dataset EGAD00001015413

• scDNA-seq for 'Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma'

  Neuroblastoma (NB) is one of the most lethal childhood cancers due its propensity to treatment resistance. By spatial mapping of subclone geographies before and after chemotherapy across 89 tumor regions from 12 NBs, we find that densely packed territories of closely related subclones present at diagnosis are replaced under effective treatment by islands of distantly related survivor subclones, originating from a different most recent ancestor compared to lineages dominating before treatment. Conversely, in tumors that progressed under treatment, ancestors of subclones dominating later in disease are present already at diagnosis. Chemotherapy treated xenografts and cell culture models replicates these two contrasting scenarios and shows branching evolution to be a constant feature of proliferating NB cells. Phylogenies based on whole genome sequencing of 505 individual NB cells indicate that a rich repertoire of parallel subclones, emerges already with the first oncogenic mutations and lays the foundation for clonal replacement under treatment.

  Dataset EGAD00001015414