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• A118830A

  Whole genome sequencing for single cells for library A118830A 912 cells; filetype=bam

  Dataset EGAD00001007604

• Single Cell Genome Sequence for DLP+ library A118808A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1096B passage 1 on DLP+ library A118808A

  Dataset EGAD00001009440

• A96175C

  Whole genome sequencing for single cells for library A96175C 1473 samples; filetype=bam

  Dataset EGAD00001008243

• A96186C

  Whole genome sequencing for single cells for library A96186C 525 samples; filetype=bam

  Dataset EGAD00001008250

• A96130B

  Whole genome sequencing for single cells for library A96130B 1267 cells; filetype=bam

  Dataset EGAD00001007114

• 10x Genomics Single Cell Gene Expression for SA1054

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 83.86

  Dataset EGAD00001009113

• 10x Genomics Single Cell Gene Expression for SA1096BX1XB02037

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009137

• 10x Genomics Single Cell Gene Expression for OV2295(R2)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line OV2295(R2)

  Dataset EGAD00001009144

• Single Cell Genome Sequence for DLP+ library A96180A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 6 on DLP+ library A96180A

  Dataset EGAD00001009463

• 10x Genomics Single Cell Gene Expression for SA1035X6XB03211

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 6

  Dataset EGAD00001009150

• 10x Genomics Single Cell Gene Expression for TOV2295(R)

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma cell line TOV2295(R)

  Dataset EGAD00001009158

• A96183C

  Whole genome sequencing for single cells for library A96183C 1036 samples; filetype=bam

  Dataset EGAD00001008247

• A95697B

  Whole genome sequencing for single cells for library A95697B 1233 cells; filetype=bam

  Dataset EGAD00001007610

• A110673B

  Whole genome sequencing for single cells for library A110673B 1153 cells; filetype=bam

  Dataset EGAD00001007603

• A96115B

  Whole genome sequencing for single cells for library A96115B 1201 cells; filetype=bam

  Dataset EGAD00001007112

• Illumina genome sequencing data for HICF2 craniosynostosis families (Genome Medicine)

  BAM files for two families recruited to the HICF2 genome sequencing project due to craniosynostosis. One family is a singleton and the other is an affected mother-daughter duo.

  Dataset EGAD00001011373

• BLUEPRINT September 2016, ATAC-seq for bone marrow, on Genome GRCh38

  ATAC-seq data for 4 sample(s) from bone marrow, on Genome GRCh38. 4 run(s), 4 experiment(s), 4 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002710

• A98253A

  Whole genome sequencing for single cells for library A98253A 1250 cells; filetype=bam

  Dataset EGAD00001007629

• Single Cell Genome Sequence for DLP+ library A96130A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 8 on DLP+ library A96130A

  Dataset EGAD00001009454

• Single Cell Genome Sequence for DLP+ library A96154A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1135, patient SA1162SA on DLP+ library A96154A

  Dataset EGAD00001009456

• Single Cell Genome Sequence for DLP+ library A96113A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage on DLP+ library A96113A

  Dataset EGAD00001009453

• Single Cell Genome Sequence for DLP+ library A96175A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 7 on DLP+ library A96175A

  Dataset EGAD00001009461

• A96120A

  Whole genome sequencing for single cells for library A96120A 1143 cells; filetype=bam

  Dataset EGAD00001007640

• Single Cell Genome Sequence for DLP+ library A95652B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A95652B

  Dataset EGAD00001009327

• A95623B

  Whole genome sequencing for single cells for library A95623B 1363 cells; filetype=bam

  Dataset EGAD00001007608

• A96155C

  Whole genome sequencing for single cells for library A96155C 1316 cells; filetype=bam

  Dataset EGAD00001007617

• A110673A

  Whole genome sequencing for single cells for library A110673A 1089 cells; filetype=bam

  Dataset EGAD00001007602

• Single Cell Genome Sequence for DLP+ library A96205B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1049A passage 1 on DLP+ library A96205B

  Dataset EGAD00001009471

• A108732A

  Whole genome sequencing for single cells for library A108732A 1139 cells; filetype=bam

  Dataset EGAD00001007592

• A110618A

  Whole genome sequencing for single cells for library A110618A 1184 cells; filetype=bam

  Dataset EGAD00001007599

• Exome and Targeted sequencing of GZL

  Tumor and matching normal exomes for 28 GZL cases (n=56) and targeted capture sequencing for 42 GZL cases with 3 matching normals and 2 pooled normals (n=47)

  Dataset EGAD00001006328

• Single Cell Genome Sequence for DLP+ library A95717B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050D passage 1 on DLP+ library A95717B

  Dataset EGAD00001009489

• 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

• A96149B

  Whole genome sequencing for single cells for library A96149B 1792 samples; filetype=bam

  Dataset EGAD00001008235

• Single Cell Genome Sequence for DLP+ library A96161A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96161A

  Dataset EGAD00001009457

• 10x Genomics Single Cell Gene Expression for SA1055

  10x Genomics Single Cell Gene Expression for Telomerase immortalized breast epithelium cell line 184-hTERT-22 L9 112.109

  Dataset EGAD00001009111

• 10x Genomics Single Cell Gene Expression for SA1053FX1XB01611

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

  Dataset EGAD00001009128

• 10x Genomics Single Cell Gene Expression for SA1096CX1XB02039

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

  Dataset EGAD00001009136

• 10x Genomics Single Cell Gene Expression for SA1035X5XB03021

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA1035 passage 5

  Dataset EGAD00001009153

• A96118A

  Whole genome sequencing for single cells for library A96118A 1193 cells; filetype=bam

  Dataset EGAD00001007113

• Whole exome sequencing of human and mouse sarcoma samples for personalized therapy

  Whole exome sequencing of human and mouse sarcoma samples for creation of personalized therapy options. Tissues were sequenced directly; no interventions or alterations were made to the tissue samples

  Dataset EGAD00001004885

• 10x Genomics Single Cell Gene Expression for SA1051DX1XB01482

  10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

  Dataset EGAD00001009133

• Single Cell Genome Sequence for DLP+ library A118816A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1180C passage 1 on DLP+ library A118816A

  Dataset EGAD00001009444

• Single Cell Genome Sequence for DLP+ library A96200B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052D passage 1 on DLP+ library A96200B

  Dataset EGAD00001009470

• Single Cell Genome Sequence for DLP+ library A96194A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053B passage 1 on DLP+ library A96194A

  Dataset EGAD00001009468

• Single Cell Genome Sequence for DLP+ library A96194B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1053E passage 1 on DLP+ library A96194B

  Dataset EGAD00001009469

• Single Cell Genome Sequence for DLP+ library A96222A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient SA1105, patient SA1103, patient SA1106, patient SA1104 on DLP+ library A96222A

  Dataset EGAD00001009478

• Single Cell Genome Sequence for DLP+ library A96206B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1050F passage 1 on DLP+ library A96206B

  Dataset EGAD00001009472

• Single Cell Genome Sequence for DLP+ library A96207A

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051A passage 1 on DLP+ library A96207A

  Dataset EGAD00001009473

• Single Cell Genome Sequence for DLP+ library A96141A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA604 passage 8 on DLP+ library A96141A

  Dataset EGAD00001009513

• single-cell RNAseq FASTq files for three muscle-invasive bladder tumors

  single-cell RNAseq FASTq files for three muscle-invasive bladder tumors

  Dataset EGAD00001008001

• Dataset for transcriptome sequencing of chordoma cells

  This dataset contains transcriptome sequencing for 15 samples from chordoma cells. The sequencing was performed on Illumina HiSeq 4000 and Illumina NovaSeq 6000. The sequencing was always paired.

  Dataset EGAD00001015642

• RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

  RNA-Seq data for manuscript titled: CBL0137 impairs homologous recombination repair and sensitizes high-grade serous ovarian carcinoma to PARP inhibitors Sequencing

  Dataset EGAD00001009799

• KiCS WGS data for academic use only

  Data from samples that are marked for academic use only

  Dataset EGAD00001009698

• A118845B

  Whole genome sequencing for single cells for library A118845B 1209 cells; filetype=bam

  Dataset EGAD00001007098

• A98295B

  Whole genome sequencing for single cells for library A98295B 1381 cells; filetype=bam

  Dataset EGAD00001007132

• A98234A

  Whole genome sequencing for single cells for library A98234A 1240 cells; filetype=bam

  Dataset EGAD00001007626

• A118862A

  Whole genome sequencing for single cells for library A118862A 1070 cells; filetype=bam

  Dataset EGAD00001007605

• Single Cell Genome Sequence for DLP+ library A96190B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1051A passage 1 on DLP+ library A96190B

  Dataset EGAD00001009466

• Single Cell Genome Sequence for DLP+ library A96207B

  Single Cell Genome Sequence for high grade serous ovarian carcinoma patient-derived xenograft SA1052B passage 1 on DLP+ library A96207B

  Dataset EGAD00001009474

• Thymic epithelial transplantation for complete DiGeorge syndrome Spatial (2026-01-19)

  Spatial transcriptome analysis of thymic cells from children with syndromic diseases such as Trisomy 21 and inflammatory/autoimmune diseases such as myasthenia gravis. . This dataset contains all the data available for this study on 2026-01-19.

  Dataset EGAD00001015798

• Single Cell Genome Sequence for DLP+ library A98240A

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA530 passage 3 on DLP+ library A98240A

  Dataset EGAD00001009480

• Transcriptomic profiles of neuroblastoma PDXs and primary tumors

  This dataset contains bam files for RNA-seq experiments for 6 neuroblastoma PDXs (Patient Derived Xenograft) and 3 pairs of neuroblastoma tumors at diagnosis and at relapse.

  Dataset EGAD00001003393

• Whole Genome Sequencing (WGS) for St. Jude High Grade Glioma (HGG) study

  Whole Genome Sequencing (WGS) for St. Jude High Grade Glioma (HGG) study

  Dataset EGAD00001000806

• V4 panel bait design test (2018-03-07)

  Targeted gene screen of FFPEs, cell lines and primary CRC tumours for testing the new V4 Colorectal gene panel. . This dataset contains all the data available for this study on 2018-03-07.

  Dataset EGAD00001004001

• Whole exome sequencing data for patients with Bosma arhinia microphthalmia syndrome (BAMS)

  Whole exome sequencing data for patients with Bosma arhinia microphthalmia syndrome (BAMS). The dataset includes 21 samples from 7 families with BAMS; see Gordon et al, Nature Genetics, 2017.

  Dataset EGAD00001003130

• Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

  Whole Exome Sequencing (WES) for St. Jude High Grade Glioma (HGG) study

  Dataset EGAD00001000807

• Exome and Transcriptome for pan-cancer gene-drug analysis

  Total of 584 tumor specimens and/or patient-derived cells across 14 cancer types were subjected for whole-exome/targeted-exome and/or whole-transcriptome sequencing.

  Dataset EGAD00001003441

• ICGC-LIRI-JP Release 16

  RIKEN collection WGS reads for 100 HCC and matched blood samples from 50 donors submitted to ICGC for release 16

  Dataset EGAD00001000842

• BLUEPRINT release January 2015, DNase-Hypersensitivity for monocyte

  DNase-Hypersensitivity data for 2 monocyte sample(s). 4 run(s), 2 experiment(s), 2 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_dnaseseq_analysis_20140811

  Dataset EGAD00001001185

• Exome sequencing of Non-syndromic Congenital Heart Defects (2019-04-24)

  Exome sequencing of ~1,800 patients with non-syndromic Congenical Heart Defects (CHD) to identify genes enriched for damaging rare variants that increase risk of CHD . This dataset contains all the data available for this study on 2019-04-24.

  Dataset EGAD00001004972

• Exome sequencing of Non-syndromic Congenital Heart Defects (2019-04-24)

  Exome sequencing of ~1,800 patients with non-syndromic Congenical Heart Defects (CHD) to identify genes enriched for damaging rare variants that increase risk of CHD . This dataset contains all the data available for this study on 2019-04-24.

  Dataset EGAD00001004975

• A95646A

  Whole genome sequencing for single cells for library A95646A 1071 cells; filetype=bam

  Dataset EGAD00001007106

• Transcriptomic data for Human proximal tubular epithelial cell interleukin-1 receptor signalling triggers cell cycle arrest during hypoxic kidney injury

  Transcriptomic data for manuscript titled: Human proximal tubular epithelial cell interleukin-1 receptor signalling triggers cell cycle arrest during hypoxic kidney injury.

  Dataset EGAD00001015460

• Family Genomics of Bipolar Disorder

  This study examined the segregation of variants with phenotype in pedigrees harboring bipolar disorder.

  Study phs000866

• Chromatin accessibility in OCI-AML22 cells

  ATAC-seq performed in OCI-AML22 subpopulations sorted based on CD34 and CD38 status

  Dataset EGAD50000001631

• OAC RNASeq

  Please see our related publication, 'Molecular profiling to predict immunochemotherapy outcomes in esophageal adenocarcinoma'

  Study EGAS00001006468

• Mutational_signatures_and_clonal_dynamics_in_normal_human_tissues

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

  Study EGAS00001002471

• SCC tumor sequencing

  In this study we have sequenced the tumor of 28 Squamous Cell Carcinoma patients.

  Study EGAS00001003988

• Impact of genetic variants in clinical outcome of a cohort of patients with oropharyngeal squamous cell carcinoma

  Caracterization of somatic variants in patients with OpSCC

  Dataset EGAD00001006151

• Liquid Biopsy by NGS show differences in CRC stage

  Exome sequencing from cfDNA blood samples. 30 sets of 2x76 Illumina reads in Fastq format.

  Dataset EGAD00001004307

• McGill EMC Release 4 in tissue "Brodmann (1909) area 44"

  McGill EMC Release 4 in tissue "Brodmann (1909) area 44"

  Dataset EGAD00001001285

• McGill EMC Release 4 in tissue "Brodmann (1909) area 11"

  McGill EMC Release 4 in tissue "Brodmann (1909) area 11"

  Dataset EGAD00001001284

• DNA methylation analysis on PBL obtained from male patients with UC-PSC, UC and HC

  Primary sclerosing cholangitis (PSC) is a chronic inflammatory liver disease affecting the intra- and extrahepatic bile ducts, and is strongly associated with ulcerative colitis (UC). In this study, we explored the peripheral blood DNA methylome and its immune cell composition in patients with PSC-UC, UC, and healthy controls (HC) with the aim to develop a predictive assay in distinguishing patients with PSC-UC from those with UC alone. The peripheral blood DNA methylome of male patients with PSC and concomitant UC, UC and HCs was profiled using the Illumina HumanMethylation Infinium EPIC BeadChip (850K) array. Differentially methylated CpG position (DMP) and region (DMR) analyses were performed alongside gradient boosting classification analyses to discern PSC-UC from UC patients. As observed differences in the DNA methylome could be the result of differences in cellular populations, we additionally employed mass cytometry to characterize the immune cell compositions. Genome wide methylation analysis revealed no differentially methylated positions between PSC-UC and UC patients. Nonetheless, using gradient boosting we were capable of discerning PSC-UC from UC with an area under the receiver operator curve (AUROC) of 0.80. Four CpG sites annotated to the NINJ2 gene were found to strongly contribute to the predictive performance. While mass cytometry analyses corroborated the largely similar blood cell composition among patients with PSC-UC, UC and HC, a higher abundance of myeloid cells was observed in UC compared to PSC-UC patients.

  Study EGAS00001005832

• RB1 Loss Triggers Dependence on ESRRG in Retinoblastoma

  Retinoblastoma (Rb) is a deadly childhood eye cancer that is classically initiated by inactivation of the RB1 tumor suppressor. Clinical management continues to rely on nonspecific chemotherapeutic agents that are associated with treatment resistance and toxicity. Here, we analyzed whole exomes from primary Rb tumors to identify novel Rb dependencies. Several recurrent genomic aberrations implicate estrogen-related receptor gamma (ESRRG) in Rb pathogenesis. ESRRG is an essential mediator of hypoxic adaptation and cell survival in retinoblastoma, representing a promising new therapeutic target.

  Study phs002859

• The Role of GPD1L in the Pathogenesis of Brugada Syndrome

  This study performed exome sequencing on a proband with Brugada Syndrome, as well as high-density SNP array data from the proband, affected family members, and unaffected family members. The principal findings of this study were the identification of GPD1L-A280V as the only plausible variant present in a linkage region on chromosome 3, which co-segregated with the Brugada Syndrome phenotype in this family. Exome sequencing data of the proband, as well as SNP array data from the family, are available.

  Study phs003468

• Impact of allogeneic umbilical-cord derived mesenchymal stromal cells on B-cell scRNAseq in patients with systemic lupus erythematosus

  The impact of MSC(UC) on peripheral B cells from Systemic Lupus Erythematosus (SLE) patients was studied by 10X scRNAseq. This scRNAseq study encompassed 3 SLE patients at 3 time points: before or after (1 month, and 3 months) MSC injection in order to analyze B cell subsets and their DEG. The aim of this study was to observe the potential changes of B cell subsets after MSC(UC) injection in SLE patients.

  Study EGAS50000000325

• Genetic Legacy of Punan Hunter-Gatherer Groups in Indonesian Borneo

  Punan Batu (the “Cave Punan”), the last living nomadic hunter-gatherer (HG) group who still literally live under karst rock shelters in Borneo, is the least-known hunter-gatherer society in Asia. To provide insights on the origin and adaptation of the Cave Punan, here we present the autosomal genome-wide SNPs study of the Cave Punan, including other Punan groups who speak different language from the Cave Punan, which are transitioning into a more sedentary lifestyle.

  Study EGAS00001004471

• Metabolomic and transcriptomic analyses identify metabolic alterations and immune suppression in ovarian cancer

  The objective of this study is to identify metabolic alterations and related phenotypes specific to ovarian cancer by performing metabolomic analysis of plasma and tissue samples. In addition, transcriptomic analysis is conducted to investigate the relationship between metabolic status and immune-related gene expression. By integrating metabolomic and transcriptomic data, this study aims to clarify how metabolic reprogramming contributes to tumor progression and immune suppression, particularly the reduction of natural killer (NK) cell activity, in ovarian cancer.

  Study JGAS000831

• The genetic analysis of circulating tumor DNA in blood of the digestive cancer patients to investigate the prognostic factors of metastasis and reccurence.

  A Darwinian evolutionary shift occurred early in the neutral evolution of advanced colorectal carcinoma (CRC) and copy number aberrations (CNA) were essential in the transition from adenoma to carcinoma. Subsequent to the primary evolution, we now focus on the evolutionary principle of the genome to foster postoperative recurrence of CRC. SO, We compared CNA, single nucleotide variance (SNV), RNA sequences between 8 primary and 11 metastatic sites from 10 CRCR cases.

  Study JGAS000221

• Mutational Spectrums and Clinical Features of Patients with LOXHD1 Variants Identified in a 8,074 Hearing Loss Patient Cohort.

  Variants of LOXHD1 gene, which are expressed in hair cells of the cochlea and vestibule, have been reported to cause a progressive form of autosomal recessive non-syndromic hereditary hearing loss, DFNB77. In this study, genetic screening was conducted on 8,074 Japanese hearing loss patients utilizing the massively parallel DNA sequencing, to identify individuals with LOXHD1 variants and to assess their phenotypes. 28 affected individuals and 21 LOXHD1 variants were identified, among which 13 were novel variants.

  Study JGAS000192

• snRNA and snATAC analysis of cocaine use disorder in human caudate nucleus

  We investigated cell type specific changes of gene expression and chromatin accessibility in the caudate nucleus of N=6 individuals with and N=8 individuals without cocaine use disorder using postmortem human brain samples. We performed single-nuclei RNA-sequencing and single-nuclei ATAC sequencing in the same cells using the 10xMultiome platform. The N=14 tissue donors were of African-American ancestry. The cohort consists of N=5 female and N=9 male individuals.

  Study EGAS50000000480

• Catalogue Statistics

  EGA Statistics Bibliography Growth Community Archive Distribution Catalogue What is in the EGA? The European Genome-phenome Archive (EGA) overview The EGA archives and distributes the results of several types of studies. Such studies include genome-wide association studies (GWAS), different purpose sequencing and molecular diagnosis assays among others. Moreover, these studies target many different kind of diseases from cancer to neurodegenerative alterations. We summarised all this data in the charts below. The statistics are computed daily based on an updated list of studies. Each pie chart depicts a different aspect of the studies: which disease type was studied, which type of sampling method was used and what was the scope of the genomic analysis. Number of studies per disease type Studies in the EGA by disease barHorizontalChart('disease-graph', 'https://stats.ega-archive.org/catalog/by_disease') Number of studies per technology type Studies in the EGA by technology barHorizontalChart('technology-graph', '/stats/studies/technology', 'Include dbGaP') Number of studies per sample type Studies in the EGA by samples barChart('samples-graph', '/stats/studies/sample-types', 'Include dbGaP')

  Documentation about/statistics/catalogue

• H3K27ac ChIP-seq in primary inflammatory (TPP) macrophages

  We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases, and identified the molecular mechanism by which the risk haplotype increases expression of the causal gene, ETS2. This mechanism was predicted to alter enhancer activity at the disease-associated locus. We therefore performed H3K27ac ChIP-seq in inflammatory macrophages from minor and major allele homozygotes at the causal allele and investigated the effect on enhancer activity. In doing so, we mechanistically delineated how the risk haplotype increases expression of ETS2.

  Study EGAS00001007562

• Investigating genetic susceptibility to rheumatic heart disease in Oceania

  This case-control study investigated susceptibility to rheumatic heart disease in over 3,000 individuals recruited across eight Oceanian countries. Cases were patients with rheumatic heart disease and controls were members of the general population. In addition to the Illumina HumanCore-24 BeadChip genotyping, a subset of 128 samples were analysed using the higher density Illumina HumanOmniExpressExome BeadChip of which 64 were also analysed using low coverage sequencing with the Illumina HiSeq 4000 platform.

  Study EGAS00001001881

• TERT rearrangements are frequent in neuroblastoma and identify aggressive tumors

  Whole genome sequencing detected structural rearrangements of TERT in 17/75 high stage neuroblastoma with 5 cases resulting from chromothripsis. Rearrangements were associated with increased TERT expression and targeted immediate up- and down-stream regions of TERT, placing in 7 cases a super-enhancer close to the breakpoints. TERT rearrangements (23%), ATRX deletions (11%) and MYCN amplifications (37%) identify three almost non-overlapping groups of high stage neuroblastoma, each associated with very poor prognosis. This submission contains all newly sequenced samples only.

  Study EGAS00001001479

• Genetic ancestry contributes to somatic mutations in lung cancers from admixed Latin American populations

  Inherited lung cancer risk, particularly in non-smokers, is poorly understood. Genomic and ancestry analysis of 1,153 lung cancers from Latin America revealed striking associations between Native American ancestry and their somatic landscape, including tumor mutational burden (TMB), and specific driver mutations in EGFR, KRAS, and STK11. A local Native American ancestry risk score predicted EGFR and KRAS mutation frequency more strongly than global ancestry, suggesting that germline genetics (rather than environmental exposure) underlie these disparities.

  Study EGAS00001004752

• Targetable NOTCH1 rearrangements in reninoma - WGS

  Reninomas are exceedingly rare renin-secreting kidney tumours that derive from juxtaglomerular cells, specialised smooth muscle cells that reside at the vascular inlet of glomeruli. They are the central component of the juxtaglomerular apparatus which controls systemic blood pressure through the secretion of renin. We assessed somatic changes in reninoma and found structural variants that generate canonical activating rearrangements of NOTCH1, whilst removing its negative regulator, NRARP. Accordingly, in single reninoma nuclei we observed excessive renin and NOTCH1 signalling mRNAs, with a concomitant non-excess of NRARP expression. Re-analysis of previously published reninoma bulk transcriptomes further corroborates our observation of dysregulated Notch pathway signalling in reninoma. Our findings reveal NOTCH1 rearrangements in reninoma, therapeutically targetable through existing NOTCH1 inhibitors, and indicate that unscheduled Notch signalling may be a disease-defining feature of reninoma.

  Dataset EGAD00001010888

• Genomic and transcriptomic landscape of T-cell lymphoblastic lymphoma compared to T-cell acute lymphoblastic leukemia: similar subtypes and different fusions

  Due to the lower incidence of T-LBL and difficulties in obtaining diagnostic T-LBL material, extensive research on T-LBL has been hampered whereas genetic aberrations in T-ALL are thoroughly characterized. Given the similarities and differences between T-LBL and T-ALL, the question has been raised whether T-LBL and T-ALL represent two different diseases or different manifestations of the same disease. This study aims to identify the genomic and transcriptomic landscape of T-LBL and compare the findings to what is found T-ALL. Comparison of the molecular aberrations between T-LBL and T-ALL can provide insights into the overlap and differences in malignant development between the two entities, which could lead to improved risk stratification in T-LBL in order to eventually adapt T-LBL treatment protocols based on molecular-genetic prognostic factors.

  Dataset EGAD00001015357

• RESOLVE_trial_targeted_sequencing_data

  RESOLVE: Abemaciclib + Letrozole +/_- Metformin, Zotatifin, or Gedatolisib in Endometrial or Low-Grade Serous Ovarian Cancer

  Study EGAS50000001202