22938 results for "ega"

in 75.28 milliseconds.

• Molecular profile of IMFT for the identification of potential druggable targets and biomarkers predicting crizotinib response.

  The clinical phase II trial EORTC 90101 “CREATE” showed high anti-tumor activity of crizotinib, an ALK/ROS1 inhibitor, in IMFT patients. However, results suggested that other molecular targets in addition to ALK/ROS1 might also contribute to the sensitivity of this kinase inhibitor. We therefore characterized molecular profile of IMFT to identify alterations which could play a role in the response to crizotinib.

  Study EGAS00001005419

• A GWAS meta-analysis on severe acne on a European population of 26,722 individuals

  Acne vulgaris is a highly heritable common, chronic inflammatory disease of the skin. We performed a genome-wide association study of 3,823 cases and 16,144 controls followed by meta-analysis with summary statistics from a previous study, with a total sample size of 26,722. We identified 20 independent association signals at 15 risk loci, 12 of which have not been previously implicated in the disease.

  Study EGAS00001003278

• Whole genome sequencing of tumour and matched normal from patients with family history of breast cancer

  Analysis of whole genome sequencing of tumour and matched normal from familial breast cancer patients who had previously undergone clinical germline testing for variation in the BRCA1 and BRCA2 genes. The patients were either carriers of BRCA1 or BRCA2 germline pathogenic variants or non-carriers high-risk individuals (non-BRCA1/2). Somatic mutational signatures were used to study tumour aetiology of these individuals.

  Study EGAS00001003305

• RNAseq Iron-Treated iPSC-derived Microglia

  Iron accumulation in microglia has been observed in Alzheimer’s disease and other neurodegenerative disorders and is thought to contribute to disease progression through various mechanisms including neuroinflammation. To study the interaction between iron accumulation and inflammation, we treated human induced pluripotent stem cell-derived microglia (iPSC-MG) with an increasing concentration of iron, in combination with inflammatory stimuli such as interferon gamma and amyloid β, and performed RNA sequencing.

  Study EGAS00001006112

• Genomic abnormalities of TP53 define distinct risk groups of paediatric B-cell non-Hodgkin lymphoma

  TP53 alterations are associated with adverse outcome in many malignancies; however, whilst common in paediatric B-NHL, their utility as a risk classifier in this setting is unknown. We evaluated the clinical significance of TP53 abnormalities (mutations, deletion and/or copy number neutral loss of heterozygosity) in a large UK paediatric B-NHL cohort (n=95) and determined their impact on survival.

  Study EGAS00001005617

• Multiomics Characterization of Low-grade Serous Ovarian Carcinoma

  Low-grade serous ovarian carcinoma (LGSOC) is a rare tumor subtype with high case fatality rates. There is a pressing need to develop effective treatments using newly available preclinical models for therapeutic discovery and drug evaluation. In this study, we use multiomics integration of whole exome sequencing, RNA sequencing, and mass spectrometry-based proteomics on fourteen LGSOC patient derived cell lines to elucidate novel biomarkers and therapeutic vulnerabilities.

  Study EGAS00001004724

• Discriminating Th17.1 cell driven sarcoidosis-like inflammation from relapse after anti-BCMA CAR T cells in multiple myeloma

  We present a case study on sarcoidosis-like flare-up after Idecabtagen Vicleucel (Ide-cel), a BCMA targeting CAR T cell therapy, and identified a Th17.1 driven autoimmune mechanism as the biological underpinning of this phenomenon using single-cell RNA-seq analysis. Furthermore, single-cell RNA-seq allowed to discriminate between immune-mediated changes and true relapse after CAR T cell treatment.

  Study EGAS00001006133

• DNA and RNA sequencing data from Ovarian Carcinosarcoma patients from the Glasgow Cohort.

  In this study, we analysed DNA and RNA sequencing data from Ovarian Carcinosarcoma patients, from isolated carcinoma and sarcoma components and investigated DNA variants as well as gene expression. Genomic analyses from this data and further investigation from preclinical models of ovarian carcinosarcoma support the conversion theory for disease development and indicate that microtubule inhibitors could be used to suppress EMT and stimulate anti-tumour immunity.

  Study EGAS00001006605

• Study the genetic susceptibility of esophagus squamous cell carcinomas (ESCC) in high-risk area Henan Chinese

  This study utilized a genetically-enriched cohort of patients with familial ESCC from the high-risk Henan region, located near the Tai-Hang Mountain region in Northern China, to identify high penetrance ESCC predisposition genes using a comprehensive unbiased whole-exome sequencing (WES) strategy. Subsequent validate the prevalence of rare damage variants by targeted gene sequencing in a large sample size.

  Study EGAS00001003423

• Somatic L1 retrotranspositions in normal human cells

  Genomic mutations accumulate in normal cells during lifetime; however, somatic mosaicism generated by mobilization of transposable elements is not well understood. Here, we explored whole-genome sequences of single-cell expanded clones to illustrate the mutational landscape produced by L1. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 and read-through RNA expression profiles to investigate the epigenetic regulation of L1 activity.

  Study EGAS00001006213

• Gene regulation of human stimulated and cultured CD4+ Treg cells

  This dataset maps gene expression regulation in human primary regulatory CD4+ T cells (Tregs) stimulated using PMA and ionomycin or cultured without stimulus for 18 hours. It includes whole genome sequence data for ChM-seq (18 H3K4me3, 20 H3K27ac and 3 inputs), ATAC-seq (42 samples) and whole transcriptome (39 samples). All individuals were genotyped using coreExome Illumina SNP chip array (included in EGAS00001003516).

  Study EGAS00001003515

• Exome and Whole-Genome Sequencing of Central African Hunter-Gatherers and Agriculturalists

  To investigate how human populations have adapted to the equatorial rainforest, we generated 266 high-coverage exomes, analyzed in combination with 300 published exomes, from 14 populations of African rainforest hunter-gatherers and farmers, together with 40 newly-generated, low-coverage genomes. Genome scans for positive selection and signatures of polygenic selection provide evidence for local adaptation of hunter-gatherers to the African rainforest.

  Study EGAS00001003722

• SPECIAL: Dissecting the melanoma ecosystem one cell at the time during immunotherapy

  The aim of this study was to identify potential biomarkers of response to immunotherapy (anti-PD1-based) as well as gain understanding of the biological mechanism of therapy resistance (either intrinsic or acquired) in melanoma patients. Single cell RNA sequencing was performed from pre- and on-treatment (2-3 weeks after immunotherapy) metastatic biopsies from stage III and IV melanoma patients.

  Study EGAS00001006488

• A single-cell transcriptional gradient in human cutaneous memory T cells restricts Th17/Tc17 identity

  We identified a gradated transcriptional program of coordinately regulated inflammation-suppressive genes in psoriatic resident memory T cells. This dataset includes bulk RNA-seq for CRISPR-based deactivation of two core components of this inflammation-suppressive program, ZFP36L2 and ZFP36, in human PBMCs. It also includes scRNA-seq of cutaneous immune cells from psoriasis patients before and during therapeutic IL-23 blockade.

  Study EGAS00001006716

• Population_based_analysis_of_POT1_variants_in_a_cutaneous_melanoma_case_control_cohort

  Pathogenic germline variants in the protection of telomeres 1 gene (POT1) have been associated with predisposition to a range of tumor types, including melanoma, glioma, leukemia and cardioangiosarcoma. We sequenced all coding exons of the POT1 gene in 2,929 European-descent melanoma cases and 3,298 controls, identifying 43 protein-changing genetic variants. We performed functional studies on each of these variants and explored their possible contribution to disease risk.

  Study EGAS00001006870

• Vitamin C boosts DNA demethylation in TET2 germline mutation carriers

  We recently identified a family with lymphoma predisposition where a heterozygous truncating germline mutation in TET2 segregated with nodular lymphocyte predominant Hodgkin lymphoma. In a clinical trial of one year, we investigated the effects of oral 1 g/day vitamin C supplementation on DNA methylation by analyzing genome-wide DNA methylation and gene expression patterns from the family members.

  Study EGAS00001006916

• PacBio Rare Disease Study

  This study leverages PacBio HiFi long-read sequencing technology to comprehensively analyze the genomic architecture of rare diseases. By generating highly accurate, long-read sequences, we aim to resolve complex structural variants, repeat expansions, and other genomic features that are often missed by short-read sequencing. Our approach facilitates improved variant detection and interpretation, advancing the understanding of rare disease etiology and enabling more precise genetic diagnoses.

  Study EGAS00001008170

• GEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the GEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008418

• Paired RNA-Seq of fCAB treated and bisulfite treated VDH01, partly depleted for NSUN3

  Paired RNA-seq of bisulfite treated VDH01 samples control or depleted for NSUN3 (4 replicates each). The samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of fCAB treated vdh01 samples control or depleted for NSUN3(4 replicates each). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of fCAB treated VDH01 samples (3). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq. Paired RNA-seq of bisulfite treated VDH01 samples (3). the samples were prepped with NEBNext Ultra II DNA library prep kit and sequenced on MiSeq.

  Dataset EGAD00001008742

• Strand-seq of hematopoietic stem and progenitor cells along human aging

  Somatic mosaicism (SM), referring to the presence of somatic mutations in sub-populations of cells within healthy individuals, is associated with an increased risk of a variety of diseases, including cancer. Blood is at particularly high risk of SM, given its rapid turnover and functionally- heterogeneous cell-type composition. While the roles of point mutations and large-scale rearrangements in blood SM have been scrutinised in recent years, the functional impact of mosaic structural variants (mSVs) remains poorly understood. Using haplotype-resolved single-cell multi-omics based on Strand-seq technology, we explored the mSV landscape of human hematopoietic stem and progenitor cells (HSPCs).

  Dataset EGAD00001009402

• Longitudinal study of whole blood gene expression in Kenyan children exposed to malaria

  We have collected RNA samples from whole blood of Kenyan children exposed to malaria in the Kilifi region of Kenya. Collections were performed each year from 2015 until 2018. This is a follow-up study to that described in Bediako et al. (in preparation). The SIMS consortium is seeking to identifying the underlying reasons why some children are more susceptible to malaria than others. In this study we hope to track changes in children’s immune systems over time which relate to the number of malaria episodes they experience. 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 EGAD00001015405

• The transcriptomic response of skeletal muscle in life-long high-level trained and untrained men and women after acute exercise

  To investigate the influence of lifelong exercise training on the response of skeletal muscle to a bout of acute exercise we generated global transcriptomic data from long-term endurance (8 men, 8 women) and strength (8 men, 8 women) trained individuals and healthy age-matched untrained controls (8 men, 8 women). Skeletal muscle biopsies were taken from M. vastus lateralis before, directly after, and after 1h and 3hrs following acute exercise. All subjects completed one bout of acute endurance exercise and one bout of acute resistance exercise, separated by 4-8 weeks. All 384 samples were multiplexed in 4 lanes and sequenced (2x250bp paired end) on the Illumina NovaSeq 6000.

  Dataset EGAD00001008663

• COVID-19 Multiomics Atlas

  We provide a single-nuclei RNA-sequencing (snRNA-seq) dataset derived from four COVID-19 patients, generated using the 10x Chromium Next GEM Single Cell v3.1 kit. For our study, these were integrated with snRNA-seq data with 12 publicly available sc/snRNA-seq datasets, comprising organ donor lung samples (n=89) and COVID-19 lung tissue samples (n=51). Additionally, we provide a spatial transcriptomic dataset characterizing different histopathological stages of diffuse alveolar damage, across a cohort of 33 COVID-19 patients. This was generated using the Nanostring Whole Transcriptome Assay (WTA) with regions of interest (ROIs) sized 400 µm² each. This integrated multi-omics analysis of snRNA-seq, histology, and spatial transcriptomics data, is available for exploration and download via our web portal: https://covid19-multiomicatlas.cellgeni.sanger.ac.uk/.

  Dataset EGAD00001015404

• ADT/SPEX CITE-Seq performance dataset

  To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the ADT/SPEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.

  Dataset EGAD00001008419

• Evolutionary trajectories and clonal migration underlying tumor progression and lymph node metastasis in resectable lung cancer

  In this prospective study, targeted deep sequencing was performed on a total of 160 primary tumors (474 regions) and 112 lymph nodes from 125 patients with stage I-III lung cancer (LuCaTH). Progressive evolution at clonal divergence scale was observed while specific driver events were positively selected for clonal sweeps during tumor development. Between-region genetic divergence (BRGD) of tumors were assessed and positively correlated with tumor differentiation. A machine learning algorithm was employed to evaluate clinicopathological and molecular parameters of primary tumors underlying lymph node metastasis. By analyzing clonal lineages and metastatic trajectories across multiple nodal stations, we unraveled a common sequential LNM seeding pattern but with divergent modes of clonal spread.

  Dataset EGAD00001007587

• Immune profiling reveals enrichment of distinct immune signatures in oral epithelial dysplasia

  The dataset contains transcriptomic information of 36 oral potentially malignant disorders (OPMD), 14 fibroepithelial polyps (FEP), and 6 early stage oral squamous cell carcinoma (OSCC) from the Asian population. Total RNA was extracted from formalin-fixed paraffin embedded (FFPE) tissue sections. RNA libraries were prepared using the NEB NextUltra RNA kit with Illumina Ribo-Zero rRNA removal as per manufacturer’s instructions. RNA sequencing was performed on the HiSeq2500 platform to generate paired-end 150 nucleotides reads and with a coverage of 50 million reads per sample. Uploaded bam files have been mapped to the GRCh38 human genome using TopHat2. Clinical and demographic data for these patients are available from the associated publications or by request.

  Dataset EGAD00001007970

• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  38 PPTCs were sequenced using RNASeq to identify oncogenic variants in driver-unknown tumors and to explore gene expression patterns. RNA libraries were quantified by qPCR using the Kapa Library Quantification Illumina/ABI Prism Kit protocol (KAPA Biosystems). Libraries were pooled in equimolar quantities and paired-end sequenced on 2 lanes of a High Throughput Run Mode flowcell with the V4 sequencing chemistry on an Illumina HiSeq 2500 platform following Illumina’s recommended protocol to generate paired-end reads of 126-bases in length.

  Dataset EGAD00001007499

• PPGL WES dataset

  Dataset includes fastq files for WES experiments for tumor samples of PPGL patients. Paired end reads fastq files are available for 87 different samples

  Dataset EGAD00001008579

• High hyperdiploid ALL single cell whole genome sequencing

  This dataset was collected from viable bone marrow cells obtained at diagnosis from nine patients with high hyperdiploid ALL and one normal bone marrow sample. All samples were subjected to low pass single cell whole genome sequencing with the median sequencing coverage of 0.02x. Single nuclei in G0/G1 phase were isolated using a fluorescence-activated cell sorting (FACS) cytometer. DNA libraries were constructed and associated next-generation sequencing was carried out by European Research Institute for the Biology of Ageing (ERIBA), University of Groningen, University Medical Center Groningen, Groningen, The Netherlands. Further details regarding the DNA libraries construction are available by Bos et. al., 2019 (https://link.springer.com/protocol/10.1007/978-1-4939-8931-7_15).

  Dataset EGAD00001008988

• Bone marrow microenvironment of 6 newly diagnosed myeloma patients using 10X Genomics scRNA- and TCR-sequencing

  10X Genomics scRNA- and TCR-sequencing (Chromium Next GEM Single Cell 5’ Reagent Kit v1.1) was performed on the plasma cell depleted mononuclear fraction of bone marrow aspirates from 6 patients with newly diagnosed multiple myeloma. Generated gene expression libraries were paired-end sequenced on the NovaSeq 6000 S2. Generated V(D)J libraries were paired-end sequenced on the NextSeq 550.

  Dataset EGAD00001009270

• Liver CD14+CD8+ T cells scRNAseq dataset

  Sorted single CD8+T cells expressing CD14 from human liver for SMARTSeq2. Livers processed: Kucykowicz et al STAR Prot 2022:pubmed.ncbi.nlm.nih.gov/35516846/ Published: Pallett et al Nature 2022 Tissue CD14+CD8+T-cells are reprogrammed by myeloid cells and modulated by LPS A modified SMART-seq2 protocol was performed on the single flow cytometry sorted-cells as previously described58. After cDNA generation, libraries were prepared (384 cells per library) using the Illumina Nextera XT kit (Illumina). Each library was sequenced to achieve a minimum depth of 1-2 million raw reads per cell using an Illumina HiSeq 4000 using v. 4 SBS chemistry to generate 75-bp paired-end reads.

  Dataset EGAD00001009831

• Pre-neoplastic somatic mutations including MYD88L265P in lymphoplasmacytic lymphoma

  In this study, we sequenced multiple stages of the B-lineage in elderly individuals and patients with lymphoplasmacytic lymphoma to study whether mutations are accumulated in normal-cell counterparts prior to lymphoma

  Dataset EGAD00001008196

• Dataset for soft_tissue_tumor-WHOLE_GENOME

  Rare cancer sequencing data of 142 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008900

• Single-nuclei gene-expression analysis of pheochromocytoma and paraganglioma links tumor subtypes with tumor microenvironment

  This dataset contains raw sequencing reads in FASTQ format from single-nuclei (30 samples) and bulk tissue (40 samples) transcriptome sequencing of pheochromocytoma and paraganglioma tissue specimens. Additionally, data from single-nuclei sequencing of two normal adrenal medulla specimens is included.

  Dataset EGAD00001008403

• Single-cell RNA sequencing of human kidney transplant nephrectomies with chronic rejection or non-alloimmune graft injury

  This dataset contains raw single-cell RNA sequencing (scRNA-seq) data for five new kidney allograft nephrectomy samples used to construct the described in the following study: https://www.biorxiv.org/content/10.1101/2022.10.28.514222v2.full. The full description of processing is described in the manuscript. Briefly, samples were digested into a single cell suspension and run according to the 10X Genomics Chromium 5’ single cell kit (v2). Sequencing was performed using an Illumina Novaseq instrument. Samples were designated as TXN2 (EGAN00002519570, mycotic pseudoaneurysm, control dataset), TXN3 (EGAN00002235628, renal vein thrombus, control dataset), TXN5 (EGAN00002519573, chronic transplant rejection), TXN6 (EGAN00002519572, chronic pyelonephritis and renal artery stenosis, non-alloimmune graft injury dataset), TXN7 (EGAN00002519576, recurrent focal segmental glomerulosclerosis, non-alloimmune graft injury dataset).

  Dataset EGAD00001015631

• Single-cell Transcriptomic and TCR Repertoire Profiling of DENV-specific CD8+ T Cells Across Dengue Disease Severities

  This dataset contains single-cell RNA sequencing (Smart-seq2) and paired TCR repertoire data of sorted dengue virus (DENV)-specific CD8⁺ T cells from individuals with differing clinical outcomes: asymptomatic dengue (AD), dengue fever (DF), and dengue hemorrhagic fever (DHF). Samples were obtained from HLA-A11⁺ and HLA-A24⁺ individuals during acute and convalescent phases, with antigen-specific CD8⁺ T cells isolated using HLA tetramers loaded with immunodominant DENV epitopes. The study identifies phenotypically distinct T cell subsets associated with disease severity, TCR avidity, and antigen reactivity to current or prior DENV serotypes. The dataset supports the understanding of CD8⁺ T cell heterogeneity, TCR features, and potential mechanisms of CD8⁺ T cell-mediated protection versus immunopathogenesis in dengue infection.

  Dataset EGAD00001015637

• Berlin Neuroblastoma Patient Genomic Data from Targeted Sequencing for Detection of TERT rearrangement breakpoints to monitor neuroblastoma

  Our objective was to establish a liquid biopsy-based monitoring strategy for pediatric high-risk neuroblastomas that are harboring genomic TERT rearrangements at diagnosis. TERT rearrangement breakpoints are detected by a hybrid capture-based neuroblastoma DNA panel sequencing (published in PMID: 34442335) in tumor material and are reflected in cell-free tumor DNA and can serve as robust biomarkers for disease activity. Within the dataset, 5 tumors of 4 pediatric patients with a neuroblastoma were DNA sequenced. Provided are FASTQ data files, bam and bambai files, as well as breakpoint spanning and encompassing read (enspan) bam and bambai files. Sequencing bam data files are aligned to GRCh37.p13 reference genome (processed).

  Dataset EGAD00001011088

• 5 scRNA-seq with TCR Enrichment of Tumour-Involved Lymph Nodes, Malignant Seromas and Patient-Derived Xenografts from 18 T-Cell Lymphoma Patients

  This raw data contains 5' scRNA-seq with TCR enrichment data from 18 individual patients analysing cells taken from tumour-involved lymph nodes (LN), malignant seromas and patient-derived xenografts (PDX) including systemic/nodal ALK+ ALCL (n=3 PDX), BIA-ALCL (n=2 seromas), PTCL-NOS (n=5 nodal tumours), nodal T follicular helper lymphoma - angioimmunoblastic type (nTFHL-AI) (n=1), nTFHL, not otherwise specified (nTFHL, NOS, n=1), TLBL (n=5) and 1 case of Sezary Syndrome (SS, cutaneous tumour). Droplet-based 5’ scRNA-seq with TCR enrichment (10x Chromium platform) was performed for all live cells, or the viable CD45+CD3- and CD45+CD3+ fractions following cell sorting by flow cytometry.

  Dataset EGAD00001015703

• An integrated single-cell reference atlas of the human endometrium

  This dataset includes both the anchor scRNA-seq and snRNA-seq datasets used to build the Human Endometrial Cell Atlas (HECA). HECA provides a comprehensive definition of endometrial cell types and states throughout the menstrual cycle in donor with and without endometriosis. It identifies consensus cell types across datasets generated by teams worldwide, as well as previously unreported cell types, all of which are validated and mapped in situ using spatial transcriptomics. Processed data is available from ArrayExpress with accession number E-MTAB-14039. See Marečková, M., Garcia-Alonso, L., Moullet, M. et al. An integrated single-cell reference atlas of the human endometrium. Nat Genet 56, 1925–1937 (2024) https://doi.org/10.1038/s41588-024-01873-w for more information.

  Dataset EGAD00001015446

• UCSF WCDT WGS/WGBS mCRPC

  This dataset contains 29 paired FASTQ files from whole-genome bisulfite sequencing (WGBS) assay performed on mCRPC tumors. Sequencing was performed using 150nt paired reads generated by a Novaseq 6000 instrument. It also contains whole-genome sequencing bam files aligned to hg38 using BWA from 36 patients, with tumor and matched tumor-adjacent normal samples. Sequencing was generated using HiSeq X Ten.

  Dataset EGAD00001009505

• Human Skeletal Muscles Transcriptome

  We generated a large transcriptome atlas of human skeletal muscles by collecting biopsies from 6 different muscles to determine molecular signatures that may be distinct between leg muscles. The biopsies were collected from gracilis (GR), semitendinosus (ST), vastus lateralis (VL), vastus medialis (VM), rectus femoris (RF), and gastrocnemius lateralis (GL) muscles. We also investigated molecular differences within the muscle by including two biopsies from the middle and distal sides of the semitendinosus muscle (STM and STD, respectively). In total, 128 samples from 20 individuals (aged 25 ± 3.6 yr) were analyzed.

  Dataset EGAD00001008657

• Dataset for gynecologic_cancer-RNA

  Rare cancer sequencing data of 48 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008856

• Lung cancer and non-cancerous plasma cfDNA samples

  The dataset contains 90 lung cancer and 5 non-cancerous lung lesion plasma cfDNA samples collected in EDTA blood collection tubes. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001008666

• Whole exome sequencing of sequential samples from a CLL patient over the course of venetoclax treatment, BCR inhibitor treatment, and venetoclax re-treatment

  The dataset contains whole exome sequencing data (libraries prepared using the Agilent SureSelect Human All Exon V6 kit, and paired-end sequenced on Illumina HiSeq4000 (2 x 150bp)) of 6 samples taken from peripheral blood mononuclear cells (PBMCs) (Samples 1-5) and bone marrow (BM). Data are provided as fastq files. Sample 1 was taken prior to initial venetoclax treatment. Sample 2 was taken as disease progression on venetoclax. Sample 3 was taken during response to BTK and PI3K inhibitor therapy. Sample 4 and the BM sample were taken at disease progression/prior to venetoclax re-treatment. And Sample 5 was taken during venetoclax re-treatment response.

  Dataset EGAD00001008685

• Genomics characterization of BRAF-V600E colorectal cancer patients treated with anti-BRAF/EGFR

  WES files (fastQ) from 19 germline DNA, 22 tumor DNA, 5 patient-derived xenograft (PDX) DNA, and 9 plasma cfDNA) samples from 28 CRC-BRAF-mutated patients collected at baseline to anti-BRAF/EGFR therapies.

  Dataset EGAD00001008755

• Pooled Single-Cell RNA-Seq of iPSC-Derived Neural Stem Cells from ADHD and Control Individuals

  This dataset contains FASTQ files from pooled single-cell RNA sequencing (scRNA-seq) of neural stem cells (NSCs) derived from induced pluripotent stem cells (iPSCs). The iPSCs were reprogrammed using the non-integrative Sendai virus system (CytoTune-iPS 2.0), introducing OCT3/4, SOX2, KLF4, and cMYC. Donor somatic cells included keratinocytes, PBMCs, and lymphoblastoid cell lines from individuals with ADHD and age-matched healthy controls (6–18 years). iPSCs underwent standard quality control, including immunocytochemistry, qRT-PCR, mycoplasma testing, and SNP genotyping. NSCs were produced via neural induction and validated by qRT-PCR and immunostaining for PAX6, SOX2, NESTIN, TUJ1, and FOXG1. Sequencing was performed on the Illumina NovaSeq 6000.

  Dataset EGAD00001015644

• Dataset for melanoma-RNA

  Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008858

• scRNA-seq and snRNA-seq of trophoblast stem cells (TSCs) differentiation into extravillous trophoblast organoids (EVTs)

  This dataset is part of a study that aims to compare in vivo human trophoblast differentiation into EVTs to different in vitro trophoblast organoids using single-cell and single-nuclei RNA sequencing. This specific dataset includes scRNA-seq and snRNA-seq data from trophoblast stem cells (TSCs). Trophoblast stem cell (TSC) lines BTS5 and BTS11 derived by Okae and colleagues were grown as described previously (Okae et al. 2018) together with EVT differentiation media. This study shows that the main regulatory programs mediating EVT invasion in vivo are preserved in in vitro models of EVT differentiation from primary trophoblast organoids and trophoblast stem cells. Data for primary trophoblast organoids is available under E-MTAB-12650.

  Dataset EGAD00001010017

• Shallow whole genome sequencing and targeted capture sequencing data of PCNSL and PTL primary and relapse pairs

  Shallow whole genome sequencing for copy number analysis and targeted capture sequencing data for translocation and mutation anslysis of paired primary and relapse PCNSL and PTL samples

  Dataset EGAD00001008387

• Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect the cell type heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Whole exome sequencing and transcriptome analysis in various in vitro and in vivo contexts was performed to study the influence of the TME on the CRC phenotype.

  Dataset EGAD00001011173

• Whole exome and RNA sequencing data from urothelial bladder cancer patients treated with anti-PD-(L)1

  We have generated and analyzed genomic data from a cohort of metastatic urothelial carcinoma patients treated with ICI such as anti-PD-(L)1 monoclonal antibodies. The dataset contains whole exome sequencing data of 27 whole blood samples and 27 FFPE tumor samples. Further, it includes RNA sequencing data from 21 tumor samples. Following the RECIST criteria, 10 patients were classified as non-responders to the treatment, and 17 were responders. The dataset also contains a merged vcf file containing somatic mutations called by Strelka2 and Mutect2 following the gatk best practice pipeline.

  Dataset EGAD00001010324

• Follicular lymphoma shallow whole genome sequencing and targeted sequencing of lymphoma panel

  Stage I and stage III/IV Follicular lymphoma samples, shallow whole genome sequencing for copy number analysis and targeted capture sequencing for mutation and translocation analysis.

  Dataset EGAD00001008385

• NLG-LBC-05 ctDNA project sequencing data

  Low-pass whole-genome sequencing of pretherapy lymphoma cfDNA and targeted sequencing of cfDNA, tumor tissue and whole-blood samples of NLG-LBC-05 patient samples and cfDNA of nine subjects with no known cancer. Hybrid capture target enrichment; panel target and sequencing information provided in PMID:34932792. FASTQ files provided for targeted sequencing, separate sequencing runs per sample noted with prefix "run" if applicable. Sequences from DTX1 and KLHL6 targets are advised to be excluded from analyses due to PCR/plasmid contaminants of in-house origin.

  Dataset EGAD00001009337

• sWGS of OV04 patient samples for ACN rascal study

  This dataset contains 142 .bam files of shallow WGS data (~0.1X) from OV04 patient samples. Sequencing reads were aligned to the 1000 Genomes Project GRCh37-derived reference genome using the BWA aligner (v.0.07.17; CRUK-CI alignment pipeline).

  Dataset EGAD00001008121

• Dataset for hematopoietic_malignancy-RNA

  Rare cancer sequencing data of 47 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008860

• Inherited MUTYH mutations cause elevated somatic mutation rates and distinctive mutational signatures in normal human cells

  Cellular DNA damage caused by reactive oxygen species is repaired by the base excision repair (BER) pathway which includes the DNA glycosylase MUTYH. Inherited biallelic MUTYH mutations cause predisposition to colorectal adenomas and carcinoma. However, the mechanistic progression from germline MUTYH mutations to MUTYH-Associated Polyposis (MAP) is incompletely understood. Here, we sequenced normal cell DNAs from 10 individuals with MAP and study the somatic mutation burden and mutational signatures.

  Dataset EGAD00001007997

• Variation and transmission of the human gut microbiota across generations - shotgun data

  Variation and transmission of the human gut microbiota across generations - shotgun sequencing data

  Dataset EGAD00001008207

• Targeted Validation Samples

  The dataset consists of targeted sequencing data obtained from an independent cohort of 11 patients to validate discriminative DMRs (differentially methylated regions) for Acute coronary syndrome (ACS) subtypes. The cohort includes 2 healthy subjects, 4 STEMI (ST-segment elevation myocardial infarction), 3 NSTEMI (non-ST-segment elevation myocardial infarction), and 2 UA (unstable angina) patients. The sequencing panel targeted 18,831 CpGs for analysis, reaching at least 5 reads coverage for 75% of the targeted CpGs in each sample. The sequencing was performed using the NEBNext Enzymatic Methyl-seq Module and the Nonacus Cell3TMTarget: Library Preparation kit, followed by probe hybridization, capture enrichment, and sequencing on the Novaseq 6000 platform, generating 400 million reads. The dataset is in raw fastq format.

  Dataset EGAD00001010934

• RNA sequencing in primary inflammatory (TPP) macrophages treated with a MEK1/2 inhibitor

  This dataset comprises raw RNA sequencing from inflammatory (TPP) macrophages that were treated with the MEK inhibitor PD-0325901 (100nM or 500nM) or vehicle control (n=3 donors). MEK inhibitor or vehicle control was added on day 4 and cells were harvested on day 6 and lysed. RNA was extracted from cell lysates using an AllPrep DNA/RNA Mini Kit (Qiagen). Sequencing libraries were prepared from 10ng RNA using the SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara) following the manufacturer’s instructions. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 and the libraries were sequenced on a NextSeq500. Raw data are provided as 50 bp paired-end Illumina reads.

  Dataset EGAD00001011337

• Sequence data from stage I of the CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

  The dataset for the study "Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer", includes 134 bam files from hybrid capture targeted error-correction next-generation sequencing (PGDx Elio plasma resolve) from plasma cell-free DNA and matched white blood cell DNA from 35 individuals with non-small cell lung cancer on the BR.36 trial, alongside 11 bam files from targeted next generation sequencing (PGDx Elio tissue complete) of tumor DNA from 11 individuals with non-small cell lung cancer on the BR.36 trial.

  Dataset EGAD00001011359

• Single-cell RNA-seq of peripheral blood mononuclear cells in classic Hodgkin lymphoma

  Abstract: Classic Hodgkin lymphoma (cHL) is a largely MHC class I-negative tumor with recurrent 9p24.1/ PD-L1/ PD-L2 copy gains and the highest reported response rates to PD-1 blockade. We utilized scRNA sequencing to characterize the peripheral immune response to PD-1 blockade and more broadly define non-CD8+ dependent mechanisms of immune evasion in cHL. Peripheral blood mononuclear cells were obtained from 20 patients with relapsed/refractory (R/R) cHL treated with PD-1 blockade (nivolumab) on the CheckMate 205 clinical trial (paired samples from cycle 1 day 1 [C1D1] and cycle 4 day 1 [C4D1]), 11 patients with newly diagnosed, previously untreated cHL and 13 healthy donors.

  Dataset EGAD00001011360

• RCC genomic data

  whole genome sequencing data

  Dataset EGAD00001009866

• WGS short read and 10X linked read sequencing of HR Deficient breast cancers

  A set of tumor/normal paired sequencing experiments, performed in short read WGS and 10X linked read whole genomes. BAM files aligned to hg19 are provided. Sample Alias number and Subject ID reflects patient of origin. T/N distinction discriminates between tumor and normal (peripheral blood) tissue.

  Dataset EGAD00001010326

• Machine Learning Guided Signal Enrichment for Plasma Tumor-burden Monitoring Dataset

  Includes 4 Datasets: 1. 35 Control Plasma WGS samples sequenced on NovaSeq V1.0 Chemistry at the New York Genome Center. Denoted by CTRL-2XX naming scheme. 2. Plasma WGS from 17 patients with Small Cell Lung Cancer. Samples extracted at either Pretreatment or Postoperative at weeks 2 or 3. Denoted by SCLC-XX naming scheme. 3. Plasma WGS from a synthetic mixing study of a high-burden melanoma plasma sample with plasma bag, at estimated tumor concentrations of 10e-3, 10e-4, 10e-5, and 10e-6 for 2 replicates. Denoted by SM-repX naming scheme. 4. Assorted Plasma, Tumor, and Normal WGS from patients with NSCLC expressing high-burden for use in model training. Denoted by NSCLC-2XX naming scheme.

  Dataset EGAD00001011352

• Identifying autosomal recessive mutations causing neurological disorders

  The objective of this study is to resequence of targeted intervals containing autosomal recessive variants causing neurological disorders in consanguineous pedigrees. Using homozygosity mapping, three intervals of very different sizes have previously been unambiguously mapped for three different neurological diseases: 2.4Mb, 8Mb and 14.3Mb in size, for Microlissencephaly, Severe Mental Retardation and Complicated hereditary spastic paraplegia respectively. This study is a pilot to assess how well custom targeted resequencing performs across a broad size range of intervals. The study design is to use a different custom capture probe set for each interval, pulldown from a single patient from each family, and sequence 1 lane using Illumina paired-reads for each sample. Candidate variants will be followed up in the families themselves, and in patients with similar phenotypes from outbred populations

  Dataset EGAD00001000340

• Identification of rare variants associated with cardiovascular traits in Cilento isolates

  The aim of this project is to identify rare genetic variants of large effect implicated in complex diseases by focusing on the study of cardiovascular diseases and related quantitative traits in a well characterized isolated population in Cilento area, Italy. The reference panel has been selected carefully in order to maximize the imputation coverage and quality on the all population samples. The selected individuals should meet three criteria: selected individuals should be chip-genotyped and closely related to the maximum number of chip-genotyped individuals so as to maximize imputation coverage; relatedness between selected individuals should be minimal, so as to minimize redundancy in genetic information of the reference panel. We perform exome sequencing on samples from 250 individuals from the Campora and Gioi-Cardile populations.

  Dataset EGAD00001002195

• WTS data of patients diagnosed with NKTL

  Whole-transcriptome sequencing (WTS) of 36 samples from patients diagnosed with NKTL. Total RNA from snap frozen EITL tumor samples was extracted using TRIzol (Invitrogen) and purified with RNeasy Mini Kit (Qiagen) according to manufacturer’s instructions. The integrity of RNA was determined by electrophoresis using 2100 Bioanalyzer (Agilent Technologies). 500 ng of total RNA was reverse transcribed with iScript cDNA Synthesis Kit (Bio-Rad, Hercules, CA, USA). Quantification was performed using SsoFast EvaGreen Supermix and CFX96 Real-Time PCR System (both Bio-Rad). Sequencing libraries were prepared using the TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero (Illumina) and WTS was performed on HiSeq 2500 and HiSeq 3000 (Illumina) with 2x101 bp and 2x151 bp read length, respectively.

  Dataset EGAD00001005230

• VariantMedium: Sensitive and generalizable somatic point mutation calling with 3D DenseNets trained and evaluated on experimental confirmation data

  This study contains whole-exome sequencing (WES) and results of targeted deep-sequencing data of three matched tumor and normal cell lines, with two technical WES replicates each. The calls by Mutect2, Strelka2, and VariantMedium were confirmed using targeted deep sequencing on Illumina Miseq The targeted deep sequencing was performed in three runs and the results are summarized under VCF files.

  Study EGAS50000001661

• Effects of Metformin on Transcriptomic and Metabolomic Profiles in Breast Cancer Survivors Enrolled in the Randomized Placebo-Controlled MetBreCS Trial

  Metformin reduces the incidence of breast cancer in patients with obesity and type 2 diabetes. However, our knowledge of the effects of metformin on breast cancer recurrence is limited. Within the randomized double-blind placebo-controlled phase II trial MetBreCS, we examined changes in breast tissue from breast cancer survivors with BMI >25 kg/m2 after treatment with metformin. To identify metformin-regulated signaling pathways, we integrated the transcriptomic, metabolomic and steroid hormone profiles using bivariate and functional analyses. We identified MS4A1, HBA2, MT-RNR1 and MT-RNR2 expression to be differentially expressed in breast tissues from metformin-treated women. We also found metformin-associated down-regulation of EGFL6 and FDCSP in postmenopausal women. The integration of transcriptomic and metabolomic profiles revealed down-regulation of immune response genes associated with reduced levels of arginine and citrulline in the metformin-treated group. The integration of transcriptomic and steroid hormone profiles showed an enrichment of steroid hormone biosynthesis and metabolism pathways with highly negatively correlated CYP11A1 and CYP1B1 expression in breast tissue from postmenopausal metformin-treated women. Our results indicate that breast cancer survivors treated with metformin have specific changes in breast tissue gene expression that may prevent the development of new tumors. Within the randomized double-blind placebo-controlled phase II trial MetBreCS, we examined changes in breast tissue from breast cancer survivors with BMI >25 kg/m2 after treatment with metformin using bulk RNAseq (total mRNA sequencing), that is deposited in Federated EGA. The steroid hormones, and metabolomics and the insulin sensitivity serum biomarker data underlying this article may be shared upon reasonable request to the PI of the MetBreCS study (Dr. Bernardo Bonanni), following approval by the Data and Safety Monitoring Board at IEO, Milan.

  Study EGAS50000000874

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• How upcycled prostate cancer sequences enabled key findings on telomeres length

  The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

  Blog prostate-cancer-sequences-enabled-key-findings-on-telomeres-length

• Advancing fast in the analysis of circulating tumour DNA

  In cancer patients, solid tumours also release DNA fragments into the blood, and they are called Circulating Tumours DNA (ctDNA). Nowadays, the standard procedure for cancer monitoring is analysis of surgically obtained biopsies. They generate a big amount of material, but the operation is highly invasive and provide medical doctors with a single-time snapshot of the tumours, which are often highly changeable. Analysis of ctDNA, on the other hand, can provide continuous information regarding the tumour itself without the need of invasive procedures. This is why interest in this method is growing, and with it, the need for its technological optimization. Guanhua Zhu and colleagues, at the Genome Institute of Singapore, developed a methodology to quantify ctDNA burden, which means to estimate the amount of tumours derived circulating DNA among all cell-free DNA in the blood of individuals. Their work, published in Nature Communications in april 2021 and summarized in a sketch below, uses state-of-the art methods to analyse cfDNA degradation patterns at promoters and exon regions, to discern it from the DNA coming from the tumours. The bright point of their approach is that simultaneously enable for profiling of actionable cancer mutations and quantitative estimation of ctDNA burden. Their sequencing data of ctDNA has been deposited in the EGA under the accession number EGAS00001004657. This study sums up to a total of 37 of cfDNA and 36 about ctDNA present up to date in the EGA archive. The existence of cfDNA was firstly described back in 2002, while the use of ctDNA analysis in the oncological field exploded only after 2016. The approach is rapidly evolving, moving in parallel with the ever-improving sequencing technologies. Especially, the possibility to obtain high quality sequences from minimal amount of material is a crucial factor. Being able to alleviate cancer patients of disturbing and often slow-recovery procedures, while at the same time improving the quality of diagnosis and disease monitoring seems like a lot to ask. Thankfully, we are blessed with brilliant and dedicated scientists from all around the world who collaborate to make this a reality, sharing their results, knowledge and data.

  Blog advancing-fast-in-the-analysis-of-circulating-tumour-dna

• Reading about genomic analysis of pan-neuroblastoma

  There are virtually no research fields that do not benefit from the large-scale genomic analysis that are so popular nowadays. For research into diseases with highly diverse clinical behavior like pediatric neuroblastoma, nevertheless, this type of approach has been a game-changer. Samuel W. Brady and colleagues, from St. Jude Children’s Research Hospital in Memphis, have gathered data from 702 neuroblastomas which were profiled by whole genome sequencing (WGS, n = 205), whole exome sequencing (WES, n = 539), and/or RNA-Seq. Less than half of the samples were generated during this study, while the others were obtained from previous work. Part of the WES data was indeed deposited in EGA in 2012 (EGA study EGAS00001000213). A scratchy summary about the huge work from Samuel W. Brady and colleagues, published in Nature Communications this October 2020 “These findings suggest that the sympathetic nervous system, the tissue from which neuroblastoma arises, is susceptible to different oncogenic insults at different times during development, which could be explored in future investigations using animal models.” Conclude the authors, highlighting the importance of their findings. Pediatric neuroblastomas are classified according to clinical and molecular features into low, intermediate, and high risk. Age plays a critical role in the classification, with younger children having an overall better prognosis. The samples included in this study belonged to all ages and risk-groups: the aim of such set up is the identification of age-associated molecular aberrations. The authors defined a mutational landscape of pediatric neuroblastoma including rare driver events, impossible to pick with a smaller data set. Interestingly, most driver mutations' frequency was found to be age-related. Those include alterations on MYCN, TERT, PTPRD, and Ras pathway, in addition to the previously reported ATRX. In addition, the large data set allowed the authors to define co-existence relations between the mutations (mutual exclusion or co-occurrence) which is a crucial puzzle piece to unravel the mechanisms driving the pathogenesis. Enjoy this really interesting article, open source on Pubmed.

  Blog genomic-analysis-of-pan-neuroblastoma

• Youth-GEMs, the project using data to define the mental health trajectories of young people

  Mental health trajectories are shaped by genetic, cognitive, social, and environmental factors that are particularly influential during human development. How exactly the interplay between these factors is impacting mental health, however, is yet unknown. The project “Gene Environment interactions in Mental health trajectories of Youth (Youth-GEMs)”, funded by the European Commission under the Horizon Europe programme, aims to help reducing mental suffering among European youth. How do Youth-GEMs contribute to bettering mental health in young people? Youth-GEMs aims to identify specific neurological, (epi)genetic and environmental drivers on mental health trajectories of young people. To do so, the project is working on a public knowledge base on functional genomics of the developing human brain, between birth and 24 years old. Reliable predictive models for trajectories of onset and course of mental illness in young people of the general population in Europe will be developed. Additionally, a secure and FAIR data infrastructure in mental health is being produced. Engaging and empowering young people Youth-GEMs is also working on the engagement of young people in the scientific field of Psychiatry. For that, the project is developing initiatives such as Science Café, intended to create a learning community where ideas and stories are shared. The 10th Science Café will take place today, with the participation of Lauren Fromont from the EGA. How do the EGA contribute to Youth-GEMs? The contributions require careful data management and harmonisation: we are dealing with an extraordinary amount of data types, sources, and time points (since the studies are longitudinal). To analyse them together and to determine which factors and interactions are truly key to account for mental health trajectories, the variables need to be transformed in a common “language”, i.e., harmonised under a common data model. Further, to guarantee FAIRness of data storage and sharing for future projects that will further advance our knowledge in the mental health field, we are ensuring that data are processed securely but can also be discovered easily. Find out more information about the project in the Youth-GEMs website.

  Blog youth-gems-mental-health

• Breast Cancer Follow Up Series

  This study's purpose is to use data generated in whole genome and exome Breast Cancer sequencing to target specific areas in multiple other Breast Cancer samples. These areas will then be subjected to PCR in multiple cases, tagged and then pool the resultant amplicons. These amplicons will then be sequenced on the Illumina GAII. This is hoped to show the prevalence of previous findings in multiple individuals in a high throughput method.

  Study EGAS00001000002

• Illumina Human Exome (ExomeChip) genotype data from the Pomak villages in Greece (HELIC Pomak Isolate). 1040 samples all >=16 years old.

  Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies. Here we have genotyped individuals from a Greek population isolate on the Illumina HumanExome Beadchip. The HELIC (Hellenic Isolated Cohorts) Pomak collection focuses on the Pomak villages in Greece. Recruitment of this population-based sample was primarily carried out at the village medical centres. www.helic.org

  Study EGAS00001000658

• The complex SNP and CNV genetic architecture of the increased risk of congenital heart defects in Down syndrome

  Here we aimed to contribute to the description of the genetic architecture of Congenital heart defect (CHD) in Down syndrome (DS), and report the results of a genome-wide association study using samples from DS individuals with and without CHD. CHD is a common developmental defect of DS occurring in 40% of cases. This case-control GWAS includes 187 DS with CHD as cases, and 151 DS without CHD as controls.

  Study EGAS00000000129

• DO NOT USE - Whole genome sequencing of SI-NETs from five patients

  Small intestine neuroendocrine tumor (SI-NET), the most common cancer of the small bowel, often displays a curious multifocal phenotype with several intestinal tumors centered around a regional lymph node metastasis, yet the typical path of evolution of these lesions remains unclear. Here, we determined the complete genome sequences of 37 tumors from 5 patients with multifocal SI-NET, allowing elucidation of phylogenetic relationships between multiple intestinal tumors and metastases in individual patients.

  Study EGAS00001004435

• Genome-wide association study in multiple human prion diseases suggests genetic risk factors additional to PRNP

  We conducted GWAS of sporadic CJD, variant CJD, iatrogenic CJD, inherited prion disease, kuru and resistance to kuru despite attendance at mortuary feasts. After quality control we analysed 2000 samples and 6015 control individuals (provided by the Wellcome Trust Case Control Consortium and KORA-gen), for 491032-511862 SNPs in the European study. Association studies were done in each geographical and aetiological group followed by several combined analyses.

  Study EGAS00000000097

• Department of Human Genetics, Radboud University Nijmegen Medical Centre, Data Access Committee

  Dac EGAC00001000076

• Frequent mutation of the major cartilage collagen gene, COL2A1, in chondrosarcoma

  Chondrosarcoma (CHS) is a heterogeneous collection of malignant bone tumours and is the second most common primary malignancy of bone after osteosarcoma. Recent work has identified frequent, recurrent mutations in IDH1/2 in nearly half of central CHS. However, there has been little systematic genomic analysis of this tumour type and thus the contribution of other genes is unclear. Here we report comprehensive genomic analyses of 49 cases of CHS. We identified hypermutability of the major cartilage collagen COL2A1 with insertions, deletions and rearrangements identified in 37% of cases. The patterns of mutation were consistent with selection for variants likely to impair normal collagen biosynthesis. In addition we identified mutations in IDH1/2 (59%), TP53 (20%), the RB1 pathway (27%) and hedgehog signaling (22%).

  Dataset EGAD00001000358

• 13K T2D-GENES analysis files

  This data set includes the following summary level data files used for the 13k analysis of T2D-GENES data: wes.variants.list: list of variants to keep for any analysis of the exomes data wes.assoc.samples.list: list of samples to keep for association analysis wes.assoc.variants.list: list of variants to keep for association analysis wes.sv.assoc.txt: single variant association analysis results wes.gene.ptv.variants.list.txt: list of protein truncating variants to use in gene-level analysis wes.gene.ptv.assoc.txt: results from gene-level tests of protein truncating variants wes.gene.nsstrict.variants.list.txt: list of NSstrict variants to use in gene-level analysis wes.gene.nsstrict.assoc.txt: results from gene-level tests of NSstrict variants wes.gene.nsbroad.variants.list.txt: list of NSbroad variants to use in gene-level analysis wes.gene.nsbroad.assoc.txt: results from gene-level tests of NSbroad variants wes.gene.ns.variants.list.txt: list of non synonymous variants to use in gene-level analysis wes.gene.ns.assoc.txt: results from gene-level tests of non synonymous variants

  Dataset EGAD00010001188

• Counts: Brain transcriptome of hereditary cerebral haemorrhage with amyloidosis–Dutch type (HCHWA-D)

  These are the log2CPM (log2 counts per million) fragments per gene counts associated with the BAM files in EGAD00001003806, in tab separated format. Counts for 36 postmortem brain samples from 9 non-demented control subjects and 9 Hereditary cerebral hemorrhage with amyloidosis-Dutch type subjects are included (1 Frontal cortex sample and 1 Occipital cortex sample per subject). RNA samples were depleted for ribosomal RNA with the Ribo Zero Gold Human kit (Illumina) and strand specific RNA-Seq libraries were generated. Paired-end sequencing was performed on a HiSeq2500 Illumina system (2x50bp reads). Alignments were performed using GSNAP v2014-12-23 with setting "--npaths 1" on GRCh38 reference genome without the alternative contigs. Fragment per gene counting was performed using HTSeq-count v0.6.1p1 with setting "--stranded reverse". The gene annotation used for quantification were UCSC RefSeq genes for GRCh38 downloaded on 2015-07-13.

  Dataset EGAD00010001457

• UK_RCC_GWAS

  Renal cell carcinoma (RCC) cases comprised adult patients with histologically proven RCC were collected through two sources within the UK. First, 856 cases from SORCE, a MRC collection of surgically treated RCC cases ascertained through UK clinical oncology centres. Second, 189 RCC cases collected through the ICR and Royal Marsden NHS Hospitals Trust. Cases included 590 clear cell carcinomas (CCCs), 42 papillary carcinomas (PCs), 33 chromophobe carcinomas (CCs) and 19 mixed or other histological subtypes. DNA was extracted from EDTA-venous blood samples using the conventional methods and quantified using PicoGreen (Invitrogen). Cases were genotyped using the Human OmniExpress-12 BeadChip according to the manufacturer's recommendations (Illumina Inc, San Diego, CA, USA). After strict QC, 944 cases were retained. Data provided in plink format. Controls used were data from the Wellcome Trust Case Control Consortium 2 (WTCCC2) 1958 birth cohort and the UK Blood Service Control Group (available as EGAS00000000028). 

  Dataset EGAD00010002310

• GSA QCed data

  QC-ed data of 9,534 DDD Study participants, including 8,879 individuals with inferred GBR ancestry. Details of genotype QC can be found in https://www.medrxiv.org/content/10.1101/2023.04.20.23288860v1.full.pdf. Genome builds are indicated in the file name. Related individuals have not been removed. Of the 9,534 samples there are 3,148 mothers, 3,138 fathers and 3,248 probands, which form 3,099 trios. Of the 8,879 GBR samples, there are 2,931 mothers, 2,937 father and 3,011 probands, which form 2,788 trios. Most of the probands have been previously genoyped on the llumina HumanCoreExome BeadChip (EGAD00010001598) or the Illumina InfiniumCoreExome Beadchip (EGAD00010001600). All samples were genotyped on the Illumina Global Screening Array.

  Dataset EGAD00010002568

• ONGOING CHROMOSOMAL INSTABILITY ACROSS ANEUPLOID SUBTYPES OF CHILDHOOD B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA ASSOCIATES WITH DISEASE PROGRESSION

  Single-cells from primary cB-ALL samples were isolated using an inverted microscope coupled to a micromanipulator equipped with glass capillary for cell collection. A minimum of 20 cells were isolated per sample in microdrops of 2.5 μl of phosphate buffered saline (PBS) with 0.5% polyvinylpyrrolidone. Cell lysis and DNA amplification was performed using the SurePlex DNA Amplification System (Illumina). Genomic DNA was subsequently fragmented and tagged with the VeriSeq PGS transposome and the TruSeq Index adapters by PCR for library preparation (VeriSeq PGS Library Prep Kit, Illumina). Equal volumes of normalized libraries were pooled and sequenced on an Illumina MySeq platform with 1×75-bp single-end sequencing. Reads were subsequently aligned to the human reference genome (GRCh38/hg38) using Bowtie2 (version 2.2.4).

  Dataset EGAD50000000029

• Differential gene expression in the colon mucosa of irritable bowel syndrome patients with diarrhea-predominant symptoms

  The aim of this study is to characterize the pathophysiology of the irritable bowel syndrome (IBS) on the functional level and in parallel on the gene expression level. For this purpose RNAseq of mucosal biopsies was performed. The data from the differential expression analysis will be further processed by Ingenuity Pathway Analysis (IPA) software to gather Information on activated or inhibited signaling pathways in the disease.

  Study EGAS50000000046

• Multi-omic characterisation of PBMCs in IBD

  We generated 10X, droplet-based Multiome (paired RNA+ATAC) data of PBMCs in 38 IBD patients. Patients are either UC or CD patients. To test the responsiveness of the cells to bacterial stimuli, we stimulated samples with either RPMI, LPS or S. Salmonella (total: 80 samples). Single-nuclei libraries are multiplexed across donors. Genotypes are provided in this dataset to perform genetic demultiplexing, phenotypes providing mapping information to retrace donors / pools / stimulations.

  Study EGAS50000000140

• Correlative Genomic Analysis of Durvalumab plus Pazopanib Combination in Patients with Advanced Soft Tissue Sarcomas

  We conducted an open-label, phase 2 study to determine the activity of the anti-VEGF receptor tyrosine-kinase inhibitor, pazopanib, combined with the anti-PD-L1 immune checkpoint inhibitor, durvalumab, in unselected advanced sarcomas. In addition, we conducted whole exome and transcriptomic sequencing with pre-treatment tissue biopsy to correlate clinical outcomes with molecular and genomic biomarkers to identify patients who would most likely benefit from the combination treatment.

  Study EGAS50000000082

• Arcagen – thoracic malignancies

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from rare thoracic malignancies (n=102)

  Study EGAS50000000123

• Single cell and spatial transcriptomics of adult human adrenal glands

  Adrenal glands are endocrine organs secreting a variety of hormones, known to undergo tissue remodelling through constant cellular turnover. Here we employed single cell and spatial transcriptomics to investigate thoroughly adult human adrenals from 14 individuals with a focus on adrenocortical cell types and cell states. By including both male and female tissue donors of various ages, we extended the study to sexual dimorphic features of the adult gland.

  Study EGAS50000000269

• Platinum-based chemotherapy induces opposing effects on immunotherapy response-related spatial and stromal biomarkers in the bladder cancer microenvironment

  The goal of the current project was to investigate the modulation of the tumor-immune microenvironment (TME) by neo-adjuvant platinum-based chemotherapy in muscle-invasive bladder cancer. Furthermore, we aimed to focus on how this modulation affects biomarkers of response to immune checkpoint inhibitors. Additionally, we aimed to explore the differences between MVAC and gemcitabine-containing platinum-based regimens regarding their effects on the bladder TME.

  Study EGAS50000000309

• scRNA-seq of CD4+ T cells from blood and tumor of NSCLC patients

  This study explore the CD4+ T cells diversity in paired blood and tumor of 5 different NSCLC patients. After FACS-sorted of Tregs (DAPI- CD45+ CD4+ CD25hi CD127lo) and Tconvs (DAPI- CD45+ CD4+CD25lo CD127lo/hi), cells were mixed in equal proportion (fifty/fifty ratio) and processed with 10X Chromium (10X Genomics) gene expression kit (3 bloods and 2 tumors) or immunoprofiling kit (2 bloods and 3 tumors) and sequenced using Illumina platforms.

  Study EGAS50000000293

• RNA-sequencing on thyroid samples from fetuses with Down syndrome and fetuses with no genetic/developmental abnormality

  The current data pertains RNA-sequencing reads obtained from thyroid samples acquired from fetuses with Down syndrome and fetuses with no genetic/developmental abnormality. Total RNA was isolated from left lobe from thyroid samples using a hand-held homogenizer and the Promega ReliaPrep RNA Miniprep System (Thermo Fisher Scientific). RNA yield was determined with the NanoDrop Microvolume Spectrophotometer (Thermo Fisher Scientific). Fragmentation and mRNA library preparation was performed using the Kapa mRNA Hyperprep Kit (Roche, Basel, Switzerland). Libraries were equimolar pooled and quality was checked on a TapeStation system using the DNA1000 ScreenTape (Agilent Technologies, Santa Clara, CA, USA). Libraries were sequenced with poly(A) selection to sequence all messenger RNA for gene expression analysis on the NovaSeq6000 PE150 (Illumina, San Diego, CA, USA), producing at least 40M 150-bp paired-end reads per library.

  Dataset EGAD50000000387

• Genomic profiles associated with response to immunotherapy in adolescent and young adult patients with melanoma

  The patterns of immune infiltration and treatment responses are unclear due to genomic and clinicopathological differences in AYA patients compared to those of older patients, and these patterns and differences may contribute to the lack of response to immunotherapy. This study fills the research gaps in understanding the molecular profiles of AYA melanoma and the key immunosuppressive signalling pathways contributing to tumour growth and resistance to immunotherapy

  Study EGAS50000000238

• The epigenomic response of skeletal muscle in life-long high-level trained and untrained men and women after acute exercise

  To investigate the influence of lifelong exercise training on the response of skeletal muscle to a bout of acute exercise we generated targeted epigenomic data from long-term endurance (8 men) and strength (8 men) trained individuals and healthy age-matched untrained controls (8 men). Skeletal muscle biopsies were taken from M. vastus lateralis before, directly after, and 3hrs following acute exercise. Control subjects completed one bout of acute endurance exercise and one bout of acute resistance exercise, separated by 4-8 weeks, athletes completed one bout in their respective form of sports. All 96 samples were used for DNA extraction and targeted library construction using a custom Twist Biosciences panel and following EM-methylation tranformation were sequenced (2x150bp paired end) on the Illumina NovaSeq 6000.

  Dataset EGAD50000000512

• Panel sequencing of endocrine-resistant breast cancer

  Patients with endocrine-resistant breast cancer in Stockholm Sweden. DNA obtained from patients primary and relapse tumors, and tumor-free lymph nodes used as germline control. DNA was extracted from formalin-fixed paraffin-embedded tissue and sequenced by 370-gene panel-based sequencing with Kapa HyperPlus library preparation and Twist Bioscience hybrid capture. Custom bait sets (panels) from Twist Bioscience. Paired end 2x150 bp using NovaSeq X. The data is presented as fastq-files.

  Study EGAS50000000236

• scRNAseq of ARID1B+/+ (control) and ARID1B+/- human telencephalic organoids at D120

  This dataset contains scRNAseq data of human telencephalic organoids, at day 120, from 4 different sequencing runs (libraries), as follows (please see cell line clone nomenclature in original publication): 1. Library 177136: Pat.2 ARID1B+/+ clone 2c (2 organoids, E11rep_1, E11rep_2), Pat.2 ARID1B+/- clone 2a (2 organoids: B002orig_1, B002orig_2) 2. Library 178119: Pat.2 ARID1B+/+ clone 2c (3 organoids: E11rep_1, E11rep_2, E11rep_3), Pat.2 ARID1B+/- clone 2a (3 organoids: B002orig_1, B002orig_2, B002orig_3) 3. Library 178120: Pat.2 ARID1B+/+ clone 2d (3 organoids: A3rep_1, A3rep_2, A3rep_3), Pat.2 ARID1B+/- clone 2b (3 organoids: B002_F7_1, B002_F7_2, B002_F7_3) 4. Library 184337: Pat.1 ARID1B+/- clone 1a (3 organoids: B001orig_1, B001orig_2, B001orig_3), HD.1 ARID1B+/+ clone 3a (3 organoids: 176_1, 176_2, 176_3), HD.1 ARID1B+/- clone 3b (3 organoids: F10_1, F10_2, F10_3)

  Dataset EGAD50000000498

• RNA sequencing from patient-derived intestinal organoids

  uman duodenal tissues for establishing organoid cultures used in this study were sourced from de-identified surgical specimens (n = 3) of the duodenum obtained from patients who had undergone biopsy procedures unrelated to CeD at Tampere University Hospital. The protocol was approved by the Ethics Committee of Tampere University Hospital, Tampere, Finland (ETL code R18082). RNA from the duodenal organoids was isolated using an RNeasy Kit (Qiagen, Hilden, Germany) following the manufacturer’s instructions. RNA purity and concentration were measured using a NanoDrop One spectrophotometer (NanoDrop Technologies, Wilmington, Delaware, USA). Preparation of the RNA library and transcriptome sequencing was conducted by Novogene Co., LTD (Cambridge, UK). Messenger RNA was purified from total RNA using polyA selection and subjected to library construction. Sequencing was performed on an Illumina platform, and 150 bp paired-end reads were generated.

  Dataset EGAD50000000492

• LCM-isolated buccal epithelial cell sequencing

  Single buccal epithelial cells were dissected and collected on an adhesive cap with laser capture microdissection (LCM) with approximately 13-60 cells per cap. Each adhesive cap containing 13-60 cells was independently processed with QIAamp DNA micro kit (Qiagen) for DNA extraction. The NEBNext ultra II FS DNA library kit was used to prepare DNA libraries with low starting material. Paired-end whole genome sequencing reads were obtained with the NovaSeq.

  Study EGAS50000000098

• DNA methylation database for gynecological cancer detection, classification and assay development

  DNA methylation changes are associated with cancer the best predictor of the presence of cancer. In order to detect and classify gynecological cancer, we performed MeD-seq to generate DNA methylation profiles of vulvar, cervical, endometrial, fallopian tube and ovarian cancers and their associated healthy tissues. DNA methylation profiles were used to find general cancer, regional cancer and specific cancer biomarkers that can be used for cancer detection, classification and treatment monitoring.

  Study EGAS50000000417

• HGG panel sequencing

  NGS panel sequencing of pediatric high-grade gliomas (HGG), including diffuse midline gliomas and hemispheric HGG. This is a population-based dataset from the Hospital for Sick Children (Toronto, Canada), of patients <18 years of age at diagnosis, and diagnosed between 2000-2022. The goal of the study was to define the genetic drivers in pediatric HGG, including the rates of different genetic drivers, such as H3 and BRAF mutations, in a single-site population based cohort.

  Study EGAS50000000221

• Single-nuclei RNA sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  10x genomics single-nuclei RNA sequencing of 9 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. snRNA-seq was performed using the ‘Frankenstein’ protocol (dx.doi.org/10.17504/protocols.io.bqxymxpw). Briefly, nuclei were extracted from frozen tissues and subjected to fluorescence-activated nuclei sorting (FANS) using 4′,6-diamidino-2-phenylindole (DAPI). Sorting was performed using a BD FACSaria 2 instrument, sorting between 3000 and 10,000 nuclei per sample, capturing both diploid and tetraploid populations. FAN-sorted nuclei were immediately processed using either the 10x Chromium Single Cell 5’ (PN-1000006, 4 samples) or 3’ (PN-1000075, 4 samples) Library & Gel Bead Kit (10x Genomics, USA). Once processed, snRNA-seq libraries were sequenced on the Illumina Nova-Seq 6000 (Illumina, USA) using 150bp paired-end sequencing. This dataset contains raw sequencing reads in FASTQ format.

  Dataset EGAD50000000505

• Cergentis FFPE-TLC sequencing of colorectal carcinoma

  In this study, formalin-fixed paraffin-embedded targeted locus capture (FFPE-TLC) sequencing is used as a novel technology for targeted detection of tumor-specific genomic structural variants (SVs) in the primary tumor of 29 colorectal cancer patients with metastatic disease. The tumor region was macrodissected and sequenced for 29 patients, and the "normal" region of the same slide was macrodissected and sequenced for 8 of these patients. SVs were found in the common fragile site (CFS)-associated genes MACROD2, PRKN, FHIT and WWOX as well as SVs caused by three LINE transposable elements. Tumor-specificity of selected SVs was independently verified by droplet digital PCR of tumor tissue DNA and their applicability as plasma circulating tumor DNA biomarkers was demonstrated. This dataset contains the hg19 reference alignment of the FFPE-TLC sequences for all 29 colorectal cancers and 8 adjacent normals.

  Dataset EGAD50000000618

• Single-cell RNA sequencing of pediatric Hodgkin Lymphoma to study the inhibition of T cell subtypes

  Here, we applied single-cell RNA-sequencing (scRNA-seq) on isolated HRS cells and the immune cells from the same pediatric classical Hodgkin Lymphoma (cHL) tumors. Specifically, 13 cHL patients and 3 reactive lymph node control samples were included in this cohort. This allowed us to identify genes of cell surface proteins that are consistently overexpressed in HRS cells and can potentially be used as targets for antibody-drug conjugates or CAR T cells. Finally, we identify potential interactions by which HRS cells inhibit T cells, among which the Galectin-1/CD69 and HLA-DRA/LAG3 interactions. However, high levels of inter-patient heterogeneity of the interaction strength were observed. In conclusion, this study identifies new potential therapeutic targets for cHL and highlights the importance of studying heterogeneity when identifying therapy targets.

  Dataset EGAD50000000626

• Bulk RNA sequencing of human T and B cells before and after interleukin-2 immunotherapy

  Bulk RNA sequencing of flow cytometry sorted human CD4+ regulatory T (Treg), CD4+ conventional T (Tcon), CD8+ T, and CD19+ B cells from systemic lupus erythematosus patients collected at baseline (day 0, before interleukin-2 immunotherpay), day 5 (after 1 treatment cycle of interleukin-2 immunotherapy), and day 68 (after 4 treatment cycles of interleukin-2 immunotherapy). The dataset comprises files from the above-mentioned 4 immune cell subsets, collected at 3 time points (day 0, day 5, and day 68) of 12 systemic lupus erythematosus patients. Due to technical reasons, day 5 samples of patient SLE_012 could not be processed and are thus missing. The complete dataset totals in 140 raw sequencing files (fastq format).

  Dataset EGAD50000000661

• Whole genome and transcriptome sequencing of cancer of unknown primary tumours

  Whole genome and transcriptome sequencing of cancer of unknown primary tumours was used to determine yield of clinical biomarkers for a molecular guided trial or for resolving cancer type of origin. This study includes profiling of germline DNA and tumour DNA and RNA by whole genome and transcriptome sequencing. All samples are in BAM format aligned with GRCh38 reference genome. This dataset includes: 1. Whole genome sequencing (WGS) of 78 cancer of unknown primary tumour samples and 73 matched germline DNA. 2. Whole transcriptome sequencing (WTS) of 69 cancer of unknown primary tumour samples (matched to WGS cases) 3. Whole genome sequencing of 22 cell-free DNA samples from cancer of unknown primary patients and matched Germaine DNA(8 samples matched to tumour WGS)

  Dataset EGAD50000000656

• Prognostic whole-genome and transcriptome signatures in colorectal cancers

  Colorectal cancer (CRC) is caused by a sequence of somatic genomic alterations affecting driver genes in core cancer pathways1. To understand the functional and prognostic impact of cancer-causing somatic mutations, we analysed the whole genomes and transcriptomes of 1,063 primary CRCs in a population-based cohort with long-term follow-up. This study constitutes the largest integrated genome and transcriptome analysis of CRC to date, and links mutations, gene expressions and patient outcomes.

  Study EGAS50000000124

• RNA-Seq of human longitudinal whole blood samples from PCR-positive and PCR-negative recent household contacts of COVID-19 index cases.

  Little is known about the transcriptomic profile of individuals who are exposed to SARS-CoV-2 yet resist becoming PCR positive. To investigate this, longitudinal whole-blood samples were taken (0, 7, 14, and 28 days after enrolment) from PCR positive and PCR negative SARS-CoV-2-naïve household contacts who were recently exposed to a COVID-19 index. Samples were also taken from pre- and post-pandemic unexposed controls. Total RNA was extracted from PAXgene tubes before undergoing poly(A) selection followed by globin and rRNA depletion. DNA libraries were constructed using the NEBNext® Ultra™ II Directional RNA Library Prep Kit for Illumina. All samples were then sequenced across 2 flowcells of an Illumina HiSeq 4000.

  Dataset EGAD50000000684

• Characterisation of Cyr61-enriched myeloid angiogenic cells

  We previously demonstrated the enrichment of an angiogenic precursor cell population from peripheral blood mononuclear cells by CYR61, a protein of the CCN family. In vivo, CYR61 mediates the binding of leukocytes and particular monocyte populations at sites of vascular inflammation. Here, we present an in vitro enrichment system mimicking (patho)physiology and at the same time representing an effective tool for enrichment of the CYR61-binding blood cells and analyzed this cell population in depth.

  Study EGAS50000000533

• Genomic Profile of Multiple Localised Spiradenoma and Spiradenocarcinoma

  Multiple spiradenomas and spiradenocarcinoma from a single donor were subjected to exome sequencing. Tumor samples were microdissected from formalin-fixed, paraffin-embedded tissue, and genomic DNA was extracted. The DNA samples were subjected to library generation using the xGen ssDNA & Low-Input DNA Library Preparation Kit, followed by exome capture using the xGen Exome Research Panel v2. The libraries were sequenced on DNBSEQ G400RS. Reads were aligned to GRCh37 with BWA.

  Study EGAS50000000554

• Transcriptome Sequencing PPGL (2)

  RNA-Seq data (n=81) library preparation was performed as previously reported by Calsina et al 2023 using QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina (Lexogen, 015). The prepared libraries were subsequently sequenced on NovaSeq™ system (Illumina). To combine the new CNIO samples (n=81) with the CNIO+TCGA dataset generated in Calsina et al., 2023, RNA data were processed using ComBat-seq as described in that same article.

  Study EGAS50000000013

• Whole genome sequencing of pancreatic cystic fluid for early detection and diagnosis of pancreatic cancer

  Pancreatic cancer (PC) is a leading cause of cancer-related deaths globally. Accurate PC detection at early or premalignant stage, when surgery is effective, would increase survival rates and prevent unnecessary surgery or surveillance. Molecular diagnostic attempts using PCy fluid (PCyF), as a liquid biopsy, to analyze common mutations associated with PC development are yet to contribute to early diagnosis. Whole genome sequencing (WGS) is utilized in various cancers, PC inclusive, for detecting genetic changes associated with carcinogenesis, but not in PCyF due to technical limitations, including isolated DNA purity. The goal of the study was to achieve high quality of WGS from PCyF from 9 patients to enable development of signatures of malignancy. The WGS was performed using Illumina sequencing. Experimental design was at a 50x depth.

  Dataset EGAD50000000869

• Genomic landscape of metastases from 97 patients with metastatic urothelial carcinoma

  Metastatic urothelial carcinoma (mUC) is a lethal cancer, with limited therapeutic options. Large-scale studies in early settings provided critical insights into the genomic and transcriptomic characteristics of non-metastatic UC. The genomic landscape of mUC remains however unclear. Whole exome (WES) and mRNA sequencing (RNA-seq) were performed on metastatic biopsies from 111 patients with mUC. Driver genomic alterations from mUC were comparable to primary UC (TCGA data).

  Study EGAS50000000373

• Cas9-targeted-based long-read sequencing for genetic screening of RPE65 locus

  In order to compare sequencing performance of different technologies in a specific locus, we sequenced blood samples of five inherited retinal dystrophies (IRD) patients harboring a monoallelic variant in RPE65 that remained uncharacterized with: 1) Clinical exome targeted sequencing (CES), 2) whole genome sequencing (WGS), and 3) Long-read sequencing on a MinION platform where CRISPR-Cas9 guide RNA probes were designed to target a 31 kb region including the entire RPE65 locus.

  Study EGAS50000000596

• Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways

  Hematopoietic stem cell (HSC) aging involves heterochromatin reorganization. These repressive marks together with DNA methylation are essential for suppressing transposable elements (TEs). In this study we analyze heterochromatin and transcriptomic changes occurring at genes and TEs in HSCs from chronic myelomonocytic leukemia, a severe myeloid malignancy affecting the elderly, compared to age-matched cells, and in the presence or absence of a combination of epidrugs.

  Study EGAS50000000367

• Reconstitution of Human Brain Cell Diversity in Organoids via Four Protocols [scRNAseq]

  Single-cell RNA-sequencing of brain organoids at day 120 grown in four distinct growth protocols designed to generate dorsal (D) and ventral (V) forebrain, midbrain (M) and striatum (S) tissue using eight different pluripotent stem cell lines. Per per cell line-protocol combination two organoids (biological replicates) were grown. For cell line 176 the experiment was conducted in two independent biological replicates (repititions E1 and E2).

  Study EGAS50000000662

• Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways

  Hematopoietic stem cell (HSC) aging involves heterochromatin reorganization. These repressive marks together with DNA methylation are essential for suppressing transposable elements (TEs). In this study we analyze heterochromatin and transcriptomic changes occurring at genes and TEs in HSCs from chronic myelomonocytic leukemia, a severe myeloid malignancy affecting the elderly, compared to age-matched cells, and in the presence or absence of a combination of epidrugs.

  Study EGAS50000000688

• Circulating tumour DNA (ctDNA) data of High Grade Serous Ovarian Cancer Patients

  This study contains circulating tumour DNA (ctDNA) data derived from longitudinal plasma samples of High Grade Serous Ovarian Cancer (HGSC) patients belonging to the DECIDER study (NCT04846933). Ovarian cancer kills more than 40 000 women in Europe each year, and HGSC is the most common and most difficult to treat subtype of this disease. This study contains different sequencing datasets with samples from different stages during the treatment of the patients.

  Study EGAS50000000674

• WES Breast Patient-derived Tumor Organoid

  This dataset includes 18 Whole Exome Sequencing (WES) samples from 5 subjects. WES is performed on a matched pair of case/control samples, e.g., tumor/control or organoid/control. For each patient, the same control sample is used for the analysis of tumor and organoid samples. The sample name structure identifies the type of sample: <subjectId>_[TON][12]_[Case|Ctrl]_EX2; where T, O, and N refer to Tumor tissue, Organoid, and control sample, respectively. The number 1 or 2 refers to the specific tissue, and Case and Ctrl indicate a tumor tissue (or organoid) and a control sample, respectively. For example, ICSBCS007_T1_Case_EX2 is the first tumor tissue of subject ICSBCS007; ICSBCS007_O1_Case_EX2 is the tumor organoid derived from that tumor sample, and ICSBCS007_N1_Ctrl_EX2 is the matching control sample. More information can be found in the sample information table.

  Dataset EGAD50000000961

• MRC 60 snRNA-seq

  This dataset includes snRNA-seq generated from post-mortem brain and genotype from 60 individuals. The snRNA-seq data was generated using the 10X Single Cell Next GEM Chip targeting a minimum 5,000 nuclei per sample and libraries prepared using the Chromium Single Cell 3′ Library and Gel Bead v3 kit according to manufacturer’s instructions. cDNA libraries were sequenced using the Illumina NovaSeq 6000 system at a minimum sequencing depth of 30,000 paired-end reads per nucleus. Samples were pooled (max 4 per pool) and sequenced over 4 lanes. Pool-specific genotype files (containing genotype information at individual level) were used to demultiplex mapped pools into individual-level single-cell data. Donor DNA from samples processed at Imperial College were genotyped using the Illumina Infinium Global Screening Array v2.0.

  Dataset EGAD50000000965