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• Recurrent somatic JAK-STAT mutations within a novel RUNX1-mutated pedigree

  The acquisition of somatic mutations is an emerging field of investigation in familial leukemia. Currently, genetic profiles in familial MDS/AML are considered analogous to sporadic disease, although the patterns of clonal evolution within families are poorly defined. We performed whole exome profiling of tumour samples from a novel RUNX1 mutated family, to determine the stepwise evolution of MDS/AML across 4 young siblings. Three siblings developed monocytic AML/RAEB2 at 5 years of age, with hepatosplenomegaly and somatic mutations upregulating JAK-STAT signalling, the latter are typically detected in <5% of sporadic MDS/AML. Two siblings acquired the canonical JAK2 V617F mutation, while another acquired a unique missense mutation of SH2B3, a negative regulator of JAK2. Notably, 2/3 siblings demonstrated dosage amplification of these mutations due to acquired uniparental disomy of chromosomes 9p and 12q (encompassing JAK2 and SH2B3, respectively). All 4 siblings were heterozygous for the 46/1 JAK2 haplotype associated with predisposition to sporadic V617F myeloproliferative disorders, which likely influenced the acquisition of JAK2 mutations. Our findings provide further evidence that relatives with shared germline mutations may acquire somatic mutations in a non-random manner leading to convergent patterns of disease evolution.

  Study EGAS00001001862

• Exploring the role of mtDNA variation in Multiple Sclerosis in a large cohort of discordant monozygotic twins

  Several lines of evidence indicate that mitochondrial DNA (mtDNA) variants might predispose to multiple sclerosis (MS). We examined this in 49 monozygotic (MZ) twin pairs clinically discordant for MS at study entry. Since the nuclear DNA of MZ twins is identical, our study provides a unique setting to functionally associate unique mtDNA variants and skewed heteroplasmy with MS development. In order to identify mtDNA variants in the twin cohort, we deeply sequenced the mitochondrial genome in blood of all 49 MZ twin pairs using next generation sequencing (Illumina, HiSeq or MiSeq) with an average coverage depth of ~25,000 sequences per base. Heteroplasmic variants were validated using targeted deep sequencing (TDS) (Illumina, MiSeq) in DNA isolated from blood and buccal swabs. In addition, whole blood was also available of 5 additional MS-affected or healthy siblings and 1 dizygotic twin pair discordant for MS, comprising in total 6 non-identical sib pairs. Moreover, all cases were screened for pathogenic mtDNA polymerase gamma (POLG) mutations. The data provides valuable insights in the possible involvement of mtDNA variants in the pathogenesis of MS, and gives information on the segregation of heteroplasmic variants within MZ twins and non-identical siblings and across different tissues.

  Study EGAS00001001240

• Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas

  Spitzoid melanoma is a specific morphologic variant of melanoma that most commonly affects children and adolescents and ranges on the spectrum of malignancy from low-grade to overtly malignant. These tumors are generally driven by fusions of ALK, RET, NTRK1/3, MET, ROS1 and BRAF. However, in approximately 50% of cases, no genetic driver has been established. Clinical whole genome and transcriptome sequencing (RNA-Seq) of a spitzoid tumor from an adolescent revealed a novel gene fusion of MAP3K8, encoding a serine−threonine kinase that activates MEK. The patient who had exhausted all other therapeutic options was treated with a MEK inhibitor and underwent a transient clinical response. We subsequently analyzed spitzoid tumors from 49 patients by RNA-Seq and found in-frame fusions or C-terminal truncations in 33% of cases. The fusion transcripts and truncated genes all contained MAP3K8 exons 1-8 but lacked the autoinhibitory final exon. Data mining of RNA-Seq from the Cancer Genome Atlas (TCGA) uncovered analogous MAP3K8 rearrangements in 1.5% of adult melanomas. Thus, MAP3K8 rearrangements - uncovered by comprehensive clinical sequencing of a single case - are the most common genetic event in spitzoid melanoma, are present in adult melanomas, and could be amenable to MEK inhibition.

  Study EGAS00001003430

• Ewing and Ewing-like-sarcoma tumoroid biobank reveals distinct drug sensitivities: translocation makes the difference

  Ewing sarcoma (ES) and Ewing-like sarcomas (ELS) are highly aggressive tumors found in soft tissues and bone of mostly children and young adults. Despite being different in many aspects, including genetics, possible cell-of-origin, and pathology, patients with any of these entities all receive the same therapeutic regimen. Currently, there is a lack of preclinical cell models that can predict drug response of these entities in vitro. Here, we describe a pediatric ES and ELS tumor organoid (tumoroid) biobank containing tumoroids with different translocations, including EWSR1::FLI1, EWSR1::ERG, CIC::DUX4, and BCOR-rearrangements. Using histology, whole genome sequencing and RNA sequencing, we demonstrate that these tumoroids retain key properties of their matching patient tumors. In addition, we traced tumor subclones in the tumoroids across patient-matched longitudinal samples, which showed that cellular heterogeneity was maintained. We subsequently performed drug screening on the tumoroid models, which unveiled entity-specific drug sensitivity to various cytotoxic compounds and targeted compounds, including MCL-1 inhibitors for CIC::DUX4 sarcomas. Taken together, this newly established ES and ELS patient-derived tumoroid biobank generates a unique source of material for future basic cancer research and drug-screening.

  Study EGAS00001007941

• Target resequencing of LQTS-related 100 genes in Japanese patients

  Some of the fatal familial arrhythmias cause sudden death in seemingly healthy individuals. It is not easy to make a pre-symptomatic diagnosis of these diseases using only clinical examinations such as an electrocardiogram. The purpose of this study is to elucidate the cause of lethal arrhythmia and/or the genetic factors that influence its susceptibility, thereby enabling early diagnosis and selection of effective treatment methods, and preventing sudden death. The most important purpose of this study is to identify the sites of genetic abnormalities and disease-related genes in pre-symptomatic cases. If a genetic abnormality is found, it is expected that the functional abnormality can be evaluated and appropriate measures to prevent sudden death can be taken.

  Study JGAS000579

• EGAD00000000032

  NcOEDG Helsinki 1 samples

  Dataset EGAD00000000032

• EGAD00000000036

  NcOEDG Stockholm 1 samples

  Dataset EGAD00000000036

• Genome analysis of oesophageal cancer and Barrett's oesophagus

  The median survival of oesophageal cancer this year is only 13 to 19 months after diagnosis and more than 90% will die from their disease. Therefore better treatment options are needed. The likelihood of cure for early screen-detected cancers is much higher. Barrett's oesophagus is a pre-cancerous lesion associated with a 30-40 fold increased risk of developing cancer. In an attempt to detect cancer early many patients with Barrett's are enrolled into surveillance programs involving regular endoscopies. A major problem with this approach is that the prevalence of BO in the population is estimated to be around 2%, but most patients with BO will never develop cancer. We are undertaking genomic and/or transcriptomic analysis of oesophageal tumours, Barrett's oesophagus and matched normal samples. The aim is to identify oesophageal-related genomic and transcriptomic alterations, which may reveal mutational process occurring, suggest biomarkers of tumour progression and treatment and identify novel treatment strategies.

  Study EGAS00001002864

• BLUEPRINT release August 2016, RNA-Seq for memory B cell, on genome GRCh38

  RNA-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002347

• BLUEPRINT release August 2016, RNA-Seq for Acute Promyelocytic Leukemia - MS-275 (20h), on genome GRCh38

  RNA-Seq data for 1 Acute Promyelocytic Leukemia - MS-275 (20h) sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002500

• BLUEPRINT release January 2015, RNA-Seq for endothelial cell of umbilical vein (proliferating)

  RNA-Seq data for 1 endothelial cell of umbilical vein (proliferating) sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001166

• BLUEPRINT release August 2016, RNA-Seq for unswitched memory B cell, on genome GRCh38

  RNA-Seq data for 1 unswitched memory B cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002414

• BLUEPRINT release August 2016, ChIP-Seq for memory B cell, on genome GRCh38

  ChIP-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_chipseq_analysis_ebi_20160816

  Dataset EGAD00001002510

• BLUEPRINT release August 2015, RNA-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001489

• BLUEPRINT release August 2016, RNA-Seq for regulatory T cell, on genome GRCh38

  RNA-Seq data for 1 regulatory T cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002351

• BLUEPRINT release August 2016, RNA-Seq for late basophilic and polychromatophilic erythroblast, on genome GRCh38

  RNA-Seq data for 1 late basophilic and polychromatophilic erythroblast sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002402

• Cancer and germline exomes consisting of FASTQ reads from melanoma, lung and colon cancer samples

  Cancer and germline exomes consisting of FASTQ reads from 6 individuals (4 melanoma, 1 lung and 1 colon cancer). Exome sequencing was performed on illumina with a depth of 100x to 200x. 2 Melanoma datasets contain reads from 2 different tumor regions 2 Melanoma datasets contain reads from 1 tumor region and from a tumor derived cell line 1 Melanoma dataset contains reads from 2 healthy tissues Colon and lung datasets contain both 1 matched germline-tumor pair

  Dataset EGAD00001007950

• BLUEPRINT release August 2016, RNA-Seq for blast forming unit erythroid, on genome GRCh38

  RNA-Seq data for 1 blast forming unit erythroid sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002365

• BLUEPRINT release January 2015, RNA-Seq for central memory CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 central memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001175

• BLUEPRINT release August 2015, RNA-Seq for regulatory T cell, on genome GRCh38

  RNA-Seq data for 1 regulatory T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001546

• BLUEPRINT release August 2015, RNA-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001478

• BLUEPRINT release January 2015, RNA-Seq for endothelial cell of umbilical vein (resting)

  RNA-Seq data for 1 endothelial cell of umbilical vein (resting) sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001142

• BLUEPRINT release August 2016, RNA-Seq for CD8-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD8-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002289

• BLUEPRINT release August 2016, RNA-Seq for CD4-positive, alpha-beta thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD4-positive, alpha-beta thymocyte sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002299

• BLUEPRINT release January 2015, RNA-Seq for effector memory CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 effector memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001153

• BLUEPRINT release August 2015, RNA-Seq for conventional dendritic cell, on genome GRCh38

  RNA-Seq data for 1 conventional dendritic cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001540

• BLUEPRINT September 2016, ChIP-Seq for conventional dendritic cell from cord blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002948

• BLUEPRINT September 2016, ChIP-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002949

• BLUEPRINT September 2016, ChIP-Seq for memory B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002950

• BLUEPRINT release August 2014, RNA-Seq for CD8-positive, alpha-beta T cell

  RNA-Seq data for 1 CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001000912

• BLUEPRINT release January 2015, RNA-Seq for effector memory CD4-positive, alpha-beta T cell

  RNA-Seq data for 1 effector memory CD4-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001163

• BLUEPRINT release January 2015, RNA-Seq for central memory CD4-positive, alpha-beta T cell

  RNA-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001172

• BLUEPRINT release August 2015, RNA-Seq for class switched memory B cell, on genome GRCh38

  RNA-Seq data for 1 class switched memory B cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001531

• BLUEPRINT release August 2015, RNA-Seq for memory B cell, on genome GRCh38

  RNA-Seq data for 1 memory B cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001542

• BLUEPRINT release August 2016, RNA-Seq for colony forming unit erythroid, on genome GRCh38

  RNA-Seq data for 1 colony forming unit erythroid sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002509

• Genetics of Cutaneous T-Cell Lymphoma

  Mycosis fungoides (MF) is a common extranodal T-cell lymphoma primarily arising in the skin. In early disease stages, MF presents as skin patches and plaques that in some cases may progress to tumor and disperse to lymph nodes and other internal organs. The 10-year overall survival is 50% in advanced stages. Early diagnosis is difficult as the histology overlaps with features of inflammatory skin diseases. Even when the diagnosis is established, there are no prognostic markers that predict whether the disease will be aggressive or indolent. Lastly, there are no curative treatments and MF will invariably relapse, even after aggressive chemotherapy. The disease is a diagnostic, prognostic and therapeutic challenge. The main objective of this study is to address the question of tumor heterogeneity in MF. To date, MF is considered to be monoclonal, derived from a transformed, mature memory T-cell. However, clinical observations and preliminary data suggest that MF comprises multiple subclones, which may be of importance for understanding disease evolution and resistance to therapy. We plan to address this objective using Whole Exome Sequencing (WES) of MF tissue prepared by laser microdissection (LMD).

  Study phs001877

• Orthogonal proteogenomic analysis identifies the druggable PA2G4-MYC axis in 3q26 AML

  Our aim was to identify regulators of the EVI1/MECOM gene, which is the most lethal oncogenic TF and is highly expressed in AML with chromosome 3q26 abnormalities.

  Study EGAS50000000347

• Mesothelioma_Whole_Genomes

  Genomic architecture of mesothelioma parent study is project 925. This project is set up in parallel to project 925 in order to Whole genome sequence ten of the 59 tumours in that project.

  Study EGAS00001000830

• Control human putamen and Substantia Nigra

  The study is affiliated to the UKBEC sample of healthy human putamen and substantia nigra phenotype. The gender is from both male and female samples of the the phenotype.

  Study EGAS00001003065

• Effect_of_FAM50_knockout_on_the_transcriptome

  A knockout clone has been generated for both FAM50A and FAM50B; knockout of the other gene is then performed and the transcriptome is analysed to look at the effect of dual gene loss.

  Study EGAS00001004836

• Unraveling metastatic progression of breast cancer

  To reconstruct the trajectories of BC progression, we performed exome sequencing (Illumina HiSeq2000, Truseq DNA sample preparation kit v2 and Exome Enrichment Kit v2; alignement done with BWA, substitutions and indels called with GATK and DINDEL respectively) coupled to validation by Sequenom and deep re-sequencing (ongoing), as well as copy number (CN) analyses (Oncoscan, Affymetrix) on DNA from matched primary (n=1-6/pt), axillary lymph node (ALN, n=1-6 for 4 pts), local recurrence (for 1 pt) and distant metastatic (n=1-5/pt) FFPE samples obtained from an autopsy series of 10 BC pts.

  Study EGAS00001000760

• Single-cell RNA-seq of AML blasts pre and post culture

  This dataset contains 6 Fastq files from 3 samples (pre-culture (n=1), post culture in standard (n=1) or niche-llike (n=1) conditions) from 1 AML patient. They correspond to single-cell RNA sequencing on Illumina plateform of 3 libraries prepared with 10X Genomics gene expression V3.1 chemistry.

  Dataset EGAD00001008772

• BLUEPRINT release January 2015, Bisulfite-Seq for Acute myeloid leukemia

  Bisulfite-Seq data for 1 Acute myeloid leukemia sample(s). 18 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001162

• Next Generation Mendelian Genetics: Auriculocondylar syndrome (ACS)

  This project is part of an ongoing project to identify the molecular genetic basis of rare craniofacial disorders. This specific project involved the collection of DNA samples from four probands with severe manifestations of auriculocondylar syndrome and their parents. Detailed clinical phenotypic data is available on each proband. The sole purpose of this research is to identify the molecular cause(s) of auriculochondylar syndrome.

  Study phs000437

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes (TIL/Tc) could determine disease course at different stages in cancer progression. We show that the diversity of the TIL/Tc TCR at baseline is prognostic in various cancers, whereas in metastatic melanoma TIL/Tc TCR clonality at baseline is predictive for activity and efficacy of PD1 blockade immunotherapy.

  Study EGAS00001005201

• Genomics_of_acral_lentiginous_melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003740

• Genomics_of_acral_lentiginous_melanoma___RNAseq

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico.

  Study EGAS00001003758

• Genetic Epidemiology of Chronic Lymphocytic Leukemia

  Chronic lymphocytic leukemia (CLL) is a subtype of B-cell lymphoproliferative disorders (LPD), and is the most common form of adult leukemia in Caucasians in the United States. Small lymphocytic lymphoma (SLL) is also a B-cell LPD and is typically considered to be the same disease as CLL, based on pathology. We consider CLL and SLL as the same disease entity, and hereafter refer to both simply as "CLL". Using genealogical databases and cancer records, the familial clustering for CLL is one of the strongest for all cancer sites, strongly implicating germline genetic risk. We ascertained CLL cases and controls for a genomewide association study (GWAS) that was undertaken as part of the International Lymphoma Epidemiology (InterLymph) consortium GWAS. Some CLL cases are also part of extended high-risk CLLpedigrees.

  Study phs001568

• Genome and transcriptome sequence data from a neurofibromatosis type 1 tumor patient

  Genome and transcriptome sequence data from a neurofibromatosis type 1 patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015301

• Whole genome shotgun sequencing and somatic mutations data in Hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is the most common malignancy of the liver. Genomic analysis is conducted to identify genetic alterations in driver genes which are all druggable targets for cancer therapy.

  Study EGAS00001002578

• FOCUS Trial

  We studied patients with advanced colorectal cancer, starting treatment with non-curative intent. 2135 unpretreated patients were randomly assigned to three treatment strategies in the ratio 1:1:1. Strategy A (control group) was single-agent fl uorouracil (given with levofolinate over 48 h every 2 weeks) until failure, then single-agent irinotecan. Strategy B was fl uorouracil until failure, then combination chemotherapy. Strategy C was combination chemotherapy from the outset.

  Study EGAS50000000725

• BLUEPRINT release August 2015, RNA-Seq for CD3-negative, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001483

• Sequence data for study: Mobilization of tissue-resident memory CD4+ T lymphocytes from bone marrow and their contribution to a systemic secondary immune reaction

  Short Description: This study contains 7 RRBS samples, including 3 ex vivo CD4+ Trm (2 x spleen and 1 x bone marrow) and 4 blood tetanus (TT) and measles (Me) antigen-reactive memory CD4+ cells before and one day post DTaP (diphtheria-tetanus-pertussis) and MMR (measles-mumps-rubella) vaccination, respectively (1 x tetanus D0, 1 x tetanus D1, 1 x measles D0, 1 x measles D1). Technology: Illumina HiSeq 2500 Filetype: fastq format

  Dataset EGAD00001007886

• BLUEPRINT release August 2016, RNA-Seq for effector memory CD8-positive, alpha-beta T cell, terminally differentiated, on genome GRCh38

  RNA-Seq data for 1 effector memory CD8-positive, alpha-beta T cell, terminally differentiated sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002320

• BLUEPRINT release August 2015, RNA-Seq for effector memory CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 1 effector memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001512

• BLUEPRINT release August 2015, RNA-Seq for effector memory CD4-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 1 effector memory CD4-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001526

• BLUEPRINT release August 2016, RNA-Seq for CD3-negative, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD3-negative, CD4-positive, CD8-positive, double positive thymocyte sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002422

• BLUEPRINT release August 2016, RNA-Seq for central memory CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 1 central memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002482

• BLUEPRINT release August 2015, RNA-Seq for central memory CD8-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 1 central memory CD8-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001547

• BLUEPRINT release August 2016, RNA-Seq for CD3-positive, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 1 run(s), 1 experiment(s), 1 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_rnaseq_analysis_crg_20160816

  Dataset EGAD00001002525

• BLUEPRINT release August 2015, RNA-Seq for CD3-positive, CD4-positive, CD8-positive, double positive thymocyte, on genome GRCh38

  RNA-Seq data for 1 CD3-positive, CD4-positive, CD8-positive, double positive thymocyte sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001593

• BLUEPRINT September 2016, ChIP-Seq for class switched memory B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for class switched memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002951

• BLUEPRINT release August 2015, RNA-Seq for central memory CD4-positive, alpha-beta T cell, on genome GRCh38

  RNA-Seq data for 1 central memory CD4-positive, alpha-beta T cell sample(s). 1 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001543

• Understanding the genetic risk underlying racial disparities in uterine fibroids

  Fibroids affect 77% of women by onset of menopause in the U.S. and account for $2.1 billion in healthcare costs each year. Fibroids negatively impact reproductive health causing heavy and painful menses, pelvic pain and pressure, pregnancy complications, and interventions including myomectomy and hysterectomy. Until recently, tumor tissue and cell culture studies investigating fibroid growth have been the primary sources for understanding fibroid pathophysiology. Genetic analysis can provide a powerful and cost effective tool to identify etiological and causal factors, especially since a genetic predisposition to fibroids has already been documented from twin studies. As much as 69% of risk is explained by genetic factors. Racial disparities also support a role for genetics with fibroid risk. African American women have earlier age of onset, more numerous and larger fibroids with a greater lifetime incidence compared to Caucasians. We propose to identify genetic markers for risk of fibroids through a genome-wide association study (GWAS) of African American and Caucasian participants, leveraging ancestral differences to narrow down genomic regions for targeted follow- up analyses. To accomplish this we will take advantage of a unique Vanderbilt resource, the BioVU DNA databank. BioVU currently has over 122,470 adults linked to electronic medical records. From BioVU we have already identified 2,902 African American and Caucasian subjects who meet our stringent inclusion criteria to conduct a GWAS of fibroids, including pelvic imaging. Available imaging is critical, because many women with fibroids are asymptomatic and without imaging, studies may misclassify as many as 51% of women. We have also defined definitive controls who reached menopause without fibroids. We have a strong group of nationally known fibroid researchers who will provide over 10,000 samples for replication. Our first Specific Aim is to conduct a GWAS for association between common single nucleotide polymorphisms (SNPs) and fibroid risk. Using a case-control design we will perform a GWAS in 2,902 (1,451 fibroid cases and 1,451 controls) women from BioVU stratified by African American and Caucasian race. Secondary admixture mapping (AM) analyses will also be performed to identify chromosomal regions of interest to prioritize for replication. Our second Aim is to resequence chromosome regions identified from GWAS and AM to discover rare variants. Finally, in Aim 3 we will replicate SNPs selected from Aim 1 and 2 in independent samples of at least 3,230 fibroid cases and 7,097 controls. We propose an efficient and cost-effective approach to identify genetic risk factors for fibroids, by taking advantage of imaging information and DNA available through BioVU. This study represents the largest GWAS of uterine fibroids and the first among African Americans leveraging emerging technologies and new statistical approaches to conduct this study. Our proposed study will fundamentally change knowledge about fibroids and lay the ground work for breakthroughs in understanding mechanisms of fibroid formation and in identifying novel therapeutic approaches.

  Study phs001409

• WES dataset for SJMPAL011911 with different treatments

  This dataset includes whole exome sequencing (WES) data from PDX samples post-drug treatment (N=1 vehicle, N=1 gilteritinib, N=1 venetoclax and N=1 VenGilt). Bam files are provided for each sample. The VenGilt-treated sample underwent whole genome amplification using the Qiagen REPLI-g kit (#150345) prior to sequencing due to the very low cell number.

  Dataset EGAD50000001425

• BLUEPRINT release August 2014, Bisulfite-Seq for macrophage

  Bisulfite-Seq data for 1 macrophage sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000923

• BLUEPRINT release August 2014, Bisulfite-Seq for erythroblast

  Bisulfite-Seq data for 1 erythroblast sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000909

• BLUEPRINT release August 2014, Bisulfite-Seq for Plasma cell

  Bisulfite-Seq data for 1 Plasma cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000927

• BLUEPRINT release January 2015, Bisulfite-Seq for plasma cell

  Bisulfite-Seq data for 1 plasma cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001160

• Discovering the Genetic Basis of Human Neuroblastoma: A Gabriella Miller Kids First Pediatric Research Program (Kids First) Project

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Children with disseminated neuroblastoma have a very high risk of treatment failure and death despite receiving intensified chemotherapy, radiation therapy and immunotherapy. The long-term goal of our research program is to ultimately improve neuroblastoma cure rates by first comprehensively defining the genetic basis of the disease. The central hypothesis to be tested here is that neuroblastoma arises largely due to the epistatic interaction of common and rare heritable DNA variation. Here we will perform a comprehensive whole genome sequencing of 563 quartets of neuroblastoma patient germline and diagnostic tumor DNAs and germline DNAs from both parents. The case series was recently collected through a Children's Oncology Group epidemiology clinical trial and is robustly annotated with complete demographic (age, sex, race, ethnicity), clinical (e.g. age at diagnosis, stage, risk group), epidemiologic (parental dietary and exposure questionnaire) and biological (e.g. tumor MYCN status and multiple other tumor genomic measures) co-variates. Subjects were consented for genetic research and DNA is immediately available for shipment for sequencing. We propose Illumina-based whole genome sequencing in the 593 "trio" germline samples (Aim 1; due to missing parent: 487 full neuroblastoma triads, 106 child-single parent dyads = 1673 whole genome sequences) and matched diagnostic tumor DNA (Aim 2; N=366) at 30x sequencing depth (N=2039 whole genome sequences). Also in Aim 2 we will perform whole exome (100x) and RNA sequencing on the 366 tumor DNA and 228 tumor RNA samples from this cohort. Finally, we propose a pilot study of structural variation using long-range sequencing in 10 non-overlapping tumor samples chosen based on potentially relevant chromosomal alterations discovered with conventional NGS. Thus, a total of 2277 individual samples and 2655 sequences will be generated. We will use our established analytic pipeline that is currently being used to study the germline genomes of all cases sequenced through the NCI supported Therapeutically Applicable Research to Generate Effective Treatments program. We plan a three-stage analytic approach, first focusing on classic de novo and inherited Mendelian damaging alterations. We will next integrate our extensive epigenomic data from human neuroblastoma cell lines and genome-wide association study data (N=5,703 neuroblastoma cases to date) to guide a comprehensive assessment of noncoding variants that influence tumor initiation with a recently established analytic pipeline. Finally, we will utilize the tumor DNA analyses to inform relevance via somatic gain or loss of function effects at the sequence and/or copy number levels. All data generated in this project will be immediately placed into the Genomic Data Commons (GDC) and we will compute within this environment by importing our analytic pipelines into the GDC. These data will be fully integrated into the Kids First Data Resource and freely shared with all academically qualified petitioners. This comprehensive data set derived from a large and richly phenotyped series of neuroblastoma DNA quartets will be integrated with existing germline and/or tumor genomic data from over 6,000 neuroblastoma subjects (but none with matched patient-parent germline sequencing data) to provide an unparalleled opportunity to comprehensively discover the genetic basis of neuroblastoma.

  Study phs001436

• Genome and transcriptome sequence data from a neurofibromatosis type 1 (NF1) tumor patient

  Genome and transcriptome sequence data from a neurofibromatosis type 1 (NF1) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015266

• Identification of genetic polymorphism on aggressive periodontitis

  Periodontitis is an inflammatory disease with loss of gingival tissue and alveolar bone. Aggressive periodontitis is rapidly progressive form of periodontitis in young people. It has been demonstrated that the susceptibility to AgP is influenced by genetic risk factors. However few were established as a risk factor for aggressive periodontitis. To identify genetic risk factors for aggressive periodontitis in Japanese population, we conducted the exome sequence of unrelated patients.

  Study JGAS000040

• Identification of genetic polymorphism on aggressive periodontitis

  Periodontitis is an inflammatory disease with loss of gingival tissue and alveolar bone. Aggressive periodontitis is rapidly progressive form of periodontitis in young people. It has been demonstrated that the susceptibility to AgP is influenced by genetic risk factors. However few were established as a risk factor for aggressive periodontitis. To identify genetic risk factors for aggressive periodontitis in Japanese population, we conducted the exome sequence of unrelated patients.

  Study JGAS000024

• Foetal_phylogeny_8pcw___WGS_of_LCM_tissues

  This study relates to the overall project of constructing the phylogeny of foetal haematopoiesis. This is an additional project relating to pre-existing work in projects 2043, 2169, 2243 and 2244. This project is to perform WGS (to around 40X) of polyclonal LCM tissues from the 8pcw foetus that have previously undergone library prep and targeted sequencing only. This work is to address reviewers comments for the publication of this work.

  Study EGAS00001004674

• Transdisciplinary Research Into Cancer of the Lung (TRICL) - Exome Plus Targeted Sequencing

  The study was conducted under the auspices of the Transdisciplinary Research In Cancer of the Lung (TRICL) Research Team, which is a part of the Genetic Associations and MEchanisms in ONcology (GAME-ON) consortium, and associated with the International Lung Cancer Consortium (ILCCO). Ethics All participants provided written informed consent. All studies were reviewed and approved by institutional ethics review committees at the involved institutions. Sequencing data are derived from four sub-studies. The sub-studies that contributed include Harvard, Liverpool, Toronto, and IARC. The IARC and Toronto studies are described above. A description of the Harvard and Liverpool studies is provided below. Liverpool Lung Project: The Liverpool Lung Project (LLP)1 is a case control and cohort study, which has over 11,500 individuals, with detailed epidemiological, clinical and outcome data with associated specimens (i.e. tumour tissue, blood, plasma, sputum, bronchial lavage, EBUS and oral brushings). The participants have completed a detailed lifestyle questionnaire and updated data on clinical outcome and hospital events are collected through the Office of National Statistics, Cancer Registry and from Health Episode Statistics. The project is registered on the UK National Institute for Health Research (NIHR) lung cancer portfolio and has all the required ethical approvals and sponsorship arrangements in place. The LLP has detailed standard operating procedures (SOP) for all aspects of the recruitment, data, specimen collection as well as the data storage. The LLP Cohort study has 8,224 participants with blood and 7,761 with plasma samples. The LLP case-control samples have been incorporated into in a large number of international GWAS and molecular studies 2,3, methylation 4-7, microRNA 8and next generation studies 9-11, resulting in high ranking publications, as well as forming the basis for the LLP risk prediction model 12-14 which has been utilised in the UK lung cancer screening trial (UKLS) 15-17 Patient and control DNAs were derived from EDTA-venous blood samples. Harvard Samples. David Christiani at the Harvard University School of Public Health has been directing research studies to investigate etiological factors influencing lung cancer development since 1983 and has amassed a collection of 2000 controls and 5055 lung cancer cases. He has been actively collecting and storing snap frozen tumor samples since 1992. Around 1500 tumor samples have been collected and the average wet tumor yield is about 30 grams of tumor, of which 631 cases have completely annotated clinical and survival information. Pathology confirmation is provided by two pathologists. At the time of surgery, a minimum of 30 grams of wet lung tumor tissue and 30 grams of non-involved tissue from the same lobe is sectioned, flash frozen and sent to Dr. Christiani's lab for logging and storage. A blood sample for DNA and serum is collected. A structured interview by trained research staff is conducted on each case, and clinical outcomes and treatments is extracted and entered into the molecular epidemiology data base at Harvard. Fresh frozen samples have been collected from 1451 lung cancer and are available for study. Samples from this collaborative study have played key roles in major studies, including the initial finding describing EGFR mutations in lung cancer 22. Participants in this study are patients, > 18 years of age, with newly diagnosed histologically confirmed lung cancer. Samples that are included in the analysis have the following histologies: Adenocarcinoma: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3 8560/3; LCC: 8012/3, 8031/3; squamous carcinoma: 8070/3, 8071/3, 8072/3, 8074/3; and other NSCLC: 8010/3, 8020/3, 8021/3, 8032/3, 8230/3. The Toronto Study: The Toronto study was conducted in the Great Toronto Area between 1997 and 2014. Cases were recruited at the hospitals in the network of University of Toronto and Lunenfeld- Tanenbaum Research Institute. At the time of recruitment in the clinical setting, provisional diagnoses of lung carcinoma were first assigned based on clinical criteria. Diagnoses for all cases included were histologically confirmed by the reference pathologist who is a specialist in pulmonary pathology, based on review of pathology reports from surgery, biopsy or cytology samples in 100% of cases. Diagnostic classification was done initially according to ICD-9, ICD-10, and ICD for oncology-2, and subsequently converted to ICD-O-3. Tumors were grouped into the major categories included in this analysis according to primary cancer type based on the ICD-3 definitions. Controls were randomly selected from individual visiting family medicine clinics and Ministry of Finance Municipal Tax Tapes. All subjects were interviewed using a standard questionnaire and information on lifestyle risk factors, occupational history, medical and family history was collected. Blood samples were collected from more than 85% of the subjects. IARC: The IARC data are derived from case-control studies conducted in Russia and include samples that have available tissue samples. Patient and control DNAs were derived from EDTA-venous blood samples. The lung cancer patients were classified according to ICD-O-3; SQ: 8070/3, 8071/3, 8072/3, 8074/3; AD: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3, 8560/3, 8251/3, 8490/3, 8570/3, 8574/3; with tumous with overlapping histologies classified as mixed. The Lung Cancer Transdisciplinary Research Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000876 Lung Cancer Transdisciplinary Research Cohort. phs000877 Meta Analysis phs000878 CIDR Lung Cancer phs001681 Affy Axiom Array

  Study phs000876

• Synthetic - FEGA Sweden Heilsa synthetic dataset December 2023

  Synthetic - This submission contains a subset of a synthetic dataset derived from the project Heilsa Tryggvedottir - a Nordic collaboration on sharing sensitive human data. Heilsa Tryggvedottir is funded by the Nordic e-Infrastructure Collaboration (NeIC), the ELIXIR nodes of Finland, Norway, and Sweden, Computerome in Denmark, and the Estonian Scientific Computing Infrastructure (ETAIS). In the synthetic data creation process, it was attempted to strike a fine balance between the usability of the datasets (e.g. technical FEGA development, testing, user training, and basic bioinformatics) and compliance with GDPR. File names and file content (e.g. headers in fastq) are anonymized. Moreover, the X, Y, and mitochondrial sequences have been discarded from the original data since these data can be used for maternal, paternal, or ethnic origin tracing. The dataset does not follow natural haplotype distribution (inherent to imputation panels). The only inputs derived from real sequence data are variant distribution density per chromosome and learning sequencing error models. The synthetic dataset consists of two fastq files, a cram file, a vcf file, and two index files.

  Dataset EGAD50000000119

• Human liver mtDNA sequencing

  BAM files containing paired-end mtDNA sequencing data from morphologically normal human liver. Clonal CCO-deficient patches of hepatocytes were identified in human liver samples, and samples were taken along a line spanning approximately from the portal triad to the central hepatic vein. Individual BAM files are named according to their patch, line and cut, where cut 1 is nearest to the portal triad, and cuts 2, 3 etc. lying further from the portal triad. Other file types include "Bulk" samples, contain sequencing data of the remaining CCO-deficient cells that were not sampled as part of the line of cuts, and "Stroma" control samples (used for identifying germ-line variants). Sequenced on NextSeq 500 platform.

  Dataset EGAD00001007991

• DNMT3A-R882 mutations intrinsically drive dysfunctional neutropoiesis from human haematopoietic stem cells

  Clonal haematopoiesis (CH) arises from the expansion of hematopoietic stem cells (HSCs) carrying leukaemia-associated somatic mutations. CH is linked to pathological immune dysregulation and a greater risk of age-related inflammatory diseases. Yet, how CH mutations impact HSC differentiation into immune effector cells remains understudied. Here, we report a single-cell resolution functional and multi-omic investigation of HSC clonal and differentiation dynamics in individuals with DNMT3A-R882 CH. DNMT3A-R882 reshapes the clonal architecture of haematopoiesis towards an aged phylogenetic structure. Functionally, DNMT3A-R882 HSCs produce decreased monocytic output but more abundant and mature neutrophil progeny compared to WT HSCs in the same individual. Whereas DNMT3A-R882 myeloid progenitors display attenuated inflammatory transcriptional programmes, DNMT3A-R882 mature neutrophils acquire proinflammatory and immunomodulatory features typical of maladaptive immunity and CH co-morbidities. Our findings, validated in humanised mice, identify aberrant DNMT3A-R882 HSC-driven neutropoiesis as a key link between CH, immune dysregulation and risk of inflammatory disease.

  Dataset EGAD00001015750

• DERMATLAS: Hidradenoma papilliferum_RNAseq

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible.For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previously, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles.

  Dataset EGAD00001015480

• Genomic Advances in Sepsis (GAinS) genotyping

  This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 35 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected over the first five days of ICU admission to investigate how host genetics affects the individual repsonse to sepsis. DNA was extracted from buffy coat or whole blood samples using the Qiagen DNA extraction protocol, the automated Maxwell Blood purification kit (Promega), or the QIAamp Blood Midi kit protocol (Qiagen). Genotyping data were generated using the Illumina HumanOmniExpress BeadChip (295 patients), the Infinium CoreExome BeadChip (655 patients), and the Infinium Global Screening Array BeadChip (307 patients). Genotyping QC and imputation into the Haplotype Reference Consortium was perfomed within each batch. The datasets were combined and following post-imputation filtering data were available on 1168 samples.

  Dataset EGAD00001015369

• Transcriptional consequences of SETBP1 variants in developmental disorders and malignancies

  The SETBP1 gene encodes a DNA-binding nuclear protein that regulates gene expression across multiple tissues. Precise control of SETBP1 dosage is essential for normal cellular function, as both loss- and gain-of-function variants of SETBP1 can lead to severe phenotypic consequences. De novo germline gain-of-function point mutations that prolong SETBP1 half-life result in Schinzel-Giedion syndrome (SGS), an ultra-rare and severe congenital disorder associated with extensive developmental abnormalities and health complications. These SGS-associated variants cluster within a hotspot in the SKI-homology domain of SETBP1, overlapping with somatic mutations recurrently observed in myeloid leukaemia with poor prognosis. Thus far, the precise mechanisms by which these SETBP1 mutations drive disease remain largely unclear. Here, through single-cell and single-nucleus mRNA sequencing of a rare collection of primary patient samples with SGS and myeloid leukaemia, we examined the transcriptional consequences of SETBP1 gain-of-function variants in haematopoietic cells, comparing their impacts when acquired in the germline and somatically in malignancies.

  Dataset EGAD00001015482

• GoNL release 5 haplotype panel

  The samples in this panel come from 250 families: 248 parents-child trios and 2 parent-child duos. As the children do not provide additional haplotypes or population information, they were excluded from the panel. The samples present in the release are composed of 248 couples, 2 single individuals and 1 sample composed from the 2 haplotypes from the duo's children transmitted by their missing parent. The composed sample is named gonl-220c_223c.The files contain a total of 18.9M SNVs and 1.1M INDELs in autosomal chromosomes. They were generated by phasing/imputing the SNVs (a) and INDELs (b) using MVNCall. Only sites passing filters are reported. Sites filtered as part of the GoNL inaccessible genome were kept (but flagged as filtered) and still may contain true positive calls but should be used with care as they are located in parts of the genome that are less well captured (systematic under or over-covered or low-mapping quality)

  Dataset EGAD00001000744

• DERMATLAS: Hidradenoma papilliferum_WES

  Virtually no other tumour type is associated with so many different forms as skin cancer. Histologically, tumours of the skin may arise from epithelium, including epidermis, hair follicle, sebaceous or sweat gland, melanocytes, dermal-associated mesenchymal structures or tissue resident immune cells, making for a diversity of clinical presentations. Importantly, many skin tumour types have an extremely poor prognosis. Many skin tumour subtypes have never undergone molecular profiling, or if they have, targeted sequencing has been used and the number of cases analyzed has been so limited that deriving firm conclusions about the profile of driver genes, DNA mutational signatures and germline alleles has not been possible.For 70 key skin tumour subtypes defined by the World Health Organization, that have not undergone extensive genetic analysis previously, we propose to perform whole exome and transcriptome sequencing, from a range of body sites, to build a genomic atlas of dermatological tumours, including detailed maps of SNVs, copy number alterations, genome-wide methylation and expression profiles.

  Dataset EGAD00001015481

• Gene expression QTL mapping in stimulated iPSC-derived macrophages

  Immune cells sense and respond to external stimuli, initiating an inflammatory response, with genetic variants potentially altering these responses. Traditional QTL mapping often uses naïve cells, missing condition-specific variants detectable post-stimulation. Our study uses a high-throughput platform to map eQTLs across 24 conditions using iPSC-derived macrophages, identifying that 76% of eQTLs in stimulated conditions were also present in naïve cells. We found response eQTLs (reQTLs) vary widely across conditions, with rare single-condition reQTLs being overrepresented among disease-colocalizing eQTLs. This study nominates 21.7% more disease effector genes at GWAS loci through reQTL colocalization, with 38.6% not found in the GTEx catalogue, highlighting the importance of condition-specific regulatory variation in understanding disease risk alleles. Our findings underscore the value of condition-specific studies in elucidating the genetic mechanisms underlying complex diseases. 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 EGAD00001015380

• Bulk paired RNAseq of CLL patients and HD donor T cells

  The datasets consists of RNA sequencing data of T cells from CLL patients or age-matched healthy donors. In brief, CLL PBMCs are thawed, the sample is split in two, one part is left as it is and stained for sorting and from the other part is stimulated using anti-CD3/CD28 soluble antibodies. After 2 days the stimulated condition is also stained and FACS sorted. The T cell fraction from healthy donors and CLL patients at baseline and after stimulation were sent for bulk sequencing.

  Dataset EGAD50000001368

• Safety and Efficacy of Intravenous Norepinephrine for Orthostatic Hypotension

  Patients with chronic autonomic failure (CAF) often have disabling orthostatic hypotension (OH). OH in CAF patients is often associated with supine hypertension (hypertension while lying down), which can be severe. Drugs to treat OH worsen supine hypertension. Therefore, the combination of OH with supine hypertension poses a difficult therapeutic challenge. This protocol is a first step toward development of a way to maintain blood pressure during standing without worsening hypertension while lying down. The research question is will a drug (norepinephrine) given intravenously (IV) prevent blood pressure from falling in patients with orthostatic hypotension. This is a placebo controlled, blinded study of 15 patients with neurogenic orthostatic hypotension. The study consists of two experimental days per participant. On a day before the day of norepinephrine (NE) infusion, the patient undergoes head-up tilting while blood pressure is monitored. Tilt angles are increased until the patient has orthostatic symptoms, systolic pressure decreases to less than 90 mm Hg, or systolic pressure decreases by more than 80 mm Hg. On the day of NE infusion patients, receive NE and placebo with the sequence of treatments randomized. If the patient has severe supine hypertension (more than 200 mm Hg systolic), then NE is infused beginning with the patient at whatever tilt angle is required for baseline pressure to be less than 200 mm Hg. NE is infused at doses titrated to keep directly recorded systolic blood pressure at or above the baseline value during exposure to higher tilt angles. When placebo is given, angles of tilt are increased until the patient has orthostatic symptoms, systolic pressure decreases to less than 90 mm Hg, or systolic pressure decreases by more than 80 mm Hg.

  Study phs001769

• Exome sequencing of patient samples from study

  Exome sequencing data from FFPE preserved patient samples and patient-derived cultures. The goal of the study is to validate patient-derived cultures. Additional goal is to understand the relationship between omics and drug response.

  Study EGAS50000000171

• Whole transcriptome seq from patient samples

  Exome sequencing data from FFPE preserved patient samples and patient-derived cultures. The goal of the study is to validate patient-derived cultures. Additional goal is to understand the relationship between omics and drug response.

  Study EGAS50000000172

• Novel compound heterozygous mutations in UHRF1 are associated with atypical immunodeficiency, centromeric instability, and facial anomalies (ICF) syndrome with distinctive genome-wide DNA hypomethylation

  Our study goal is to reveal underlying molecular pathogenesis of Immunodeficiency, Centromeric instability, and Facial anomalies (ICF) syndrome, which is characterized by hypomethylation of centromeric/pericentromeric repeats.

  Study JGAS000559

• Whole genome sequencing for novel neuromuscular disease gene discovery

  This peripheral neuropathy patient underwent whole genome sequencing to find the cause of their disease. They were undiagnosed by current standard-of-care practice, which is neurogenetic panel screening. This is a paediatric case.

  Study EGAS00001004535

• arcOGEN_HumanCoreExome-12v1-1_subset_1

  Subset 1 of osteoarthritis cases from the arcOGEN Consortium (http://www.arcogen.org.uk/) genotyped on HumanCoreExome-12v1-1 with broader consent.

  Dataset EGAD00010000926

• BLUEPRINT release August 2014, Bisulfite-Seq for hematopoietic multipotent progenitor cell

  Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000917

• BLUEPRINT release January 2015, Bisulfite-Seq for germinal center B cell

  Bisulfite-Seq data for 1 germinal center B cell sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001203

• BLUEPRINT release January 2015, Bisulfite-Seq for memory B cell

  Bisulfite-Seq data for 1 memory B cell sample(s). 20 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001131

• BLUEPRINT release January 2015, Bisulfite-Seq for hematopoietic multipotent progenitor cell

  Bisulfite-Seq data for 1 hematopoietic multipotent progenitor cell sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001141

• BLUEPRINT release August 2014, Bisulfite-Seq for alternatively activated macrophage

  Bisulfite-Seq data for 1 alternatively activated macrophage sample(s). 10 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000920

• BLUEPRINT release August 2014, Bisulfite-Seq for germinal center B cell

  Bisulfite-Seq data for 1 germinal center B cell sample(s). 8 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000943

• BLUEPRINT release August 2015, Bisulfite-Seq for Acute Myeloid Leukemia - CTR, on genome GRCh38

  Bisulfite-Seq data for 1 Acute Myeloid Leukemia - CTR sample(s). 18 run(s), 1 experiment(s), 1 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_bisulphite_analysis_CNAG_20150820

  Dataset EGAD00001001530

• Neuroblastoma Genome-Wide Association Study (NBL-GWAS)

  Neuroblastoma is a malignancy of the developing sympathetic nervous system that most commonly affects young children and is often lethal. The etiology of this embryonal cancer is not known. We have performed a whole genome scan for association of neuroblastoma with SNP genotypes and copy number variation to discover predisposition loci. We therefore initiated a genome-wide association study (GWAS) in 2007 focused on neuroblastoma patients identified through the Children's Oncology Group (COG; 238 member institutions). Control patients for this study are children cared for at the Children's Hospital of Philadelphia (CHOP) without a diagnosis of cancer. The study was designed to collect up to 5000 neuroblastoma cases and 10,000 controls and is powered to detect common susceptibility variants in Caucasian and African American patients. Whole genome genotyping is being performed on the Illumina HH550 SNP array.

  Study phs000124

• Estonian Biobank | Estonian Genome Center, University of Tartu

  The Estonian Biobank is the population-based biobank of the Estonian Genome Centre of University of Tartu. The biobank is conducted according to the Estonian Gene Research Act and all participants have signed broad informed consent. The cohort size is currently 51,535 people from 18 years of age and up. Metabolite concentrations (over 110; NMR and MS) are available for about 12,000 subjects; metabolic follow-up has been done for more than 2000 donors. GWAS has been performed on 20,000 subjects with different Illumina arrays and 2,500 have whole exomes and 2,400 full sequence. The data for the 2,400 fully sequenced samples is available through dbGaP.

  Study phs001230