12405 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

in 45.54 milliseconds.

• Pre-neoplastic liver colonization by 11p15.5 altered mosaic cells in young children with hepatoblastoma

  Additional datasets linked to EGAS00001006692

  Dataset EGAD00001011097

• bam files Targeted BS

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001667

• Panel sequencing data of IMPACT2 patients

  Patient samples were sequenced by Foundation Medicine, Inc. (Cambridge, MA), using FoundationOne CDx, a comprehensive NGS-based in vitro diagnostic device designed to capture cancer genes.

  Dataset EGAD00001006887

• VALCAP files for Ma et al. (2019) SCMC Hybrid

  VALCAP files for Ma et al. (2019) Genome Biology (accepted) titled “Analysis of error profiles in deep next-generation sequencing data"

  Dataset EGAD00001004595

• Whole genome SMRT sequencing in the HF-GBM-Tumor-Neurosphere-Xenograft study

  This data set consists of whole genome SMRT sequencing fastqs generated from 2 xenograft samples.

  Dataset EGAD00001002264

• BAM Files MBD-SEQ

  Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  Dataset EGAD00001001668

• Expressed fusion transcripts in rare bone tumours

  mRNA-Seq on total RNA from primary osteoblastomas and phosphaturic mesenchymal tumours, focussing on fusion transcript expression

  Dataset EGAD00001000990

• Cell lines with telomere fusion-induced rearrangements

  Whole-genome somatic rearrangement and point mutation analysis in cell lines with induced telomere fusions.

  Dataset EGAD00001001629

• ORCADES 15x (2019-07-23)

  15x whole genome sequencing in samples from the isolated population of Orkney. This dataset contains all the data available for this study on 2019-07-23.

  Dataset EGAD00001005194

• WGS files for CIC paper data

  WGS files for CIC paper titled "Malignant progression of an ancestral bone marrow clone harboring a CIC-NUTM2A fusion in isolated myeloid sarcoma"

  Dataset EGAD00001009787

• Copy number profiling of pleura samples and respective tumors

  Low-coverage whole genome sequencing for the establishment of genomewide copy number alterations in pleura effusions and respective primary tumors

  Dataset EGAD00001003273

• WES files for Newman MAP3K8 melanoma

  WES files for Newman MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004566

• GENOMIC INSTABILITY IN MISMATCH REPAIR DEFICIENT COLORECTAL CANCER WES MSI Colorectal Cancer

  This dataset contains Whole Exome Sequencing of 47 MSI colorectal cancers (CRCs) and paired adjacent normal mucosa

  Dataset EGAD00001004550

• Organoid Derivation Project TGS: Release 1

  Targeted gene sequencing of cancer driver genes to determine the driver mutations present in newly-derived cancer organoid models

  Dataset EGAD00001004368

• Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks

  Whole genome sequencing data on 10 human cancer cell lines

  Dataset EGAD00001003824

• WGS files for Newman MAP3K8 melanoma

  WGS files for Newman MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004579

• Exome sequencing reads

  Exome sequencing reads of two UFM individuals and their family members (totally 11 individuals) belonging to two different Fragile X families. Alignment files in BAM format are provided.

  Dataset EGAD00001002276

• Dateset of clonal evolution in myelofibrosis

  This dataset includes bam files of tumor and paired normal samples derived from 15 patients with myelofibrosis. Tumor samples includes those before and after treatment.

  Dataset EGAD00001005282

• subset of WGS data from umbrella study EGAS00001004338, used in EGAS00001004786

  linking 58 samples/58 runs of WGS from EGAS00001004338 Umbrella study to EGAS0001004786 study

  Dataset EGAD00001006614

• HCA Organoids | Colon - Cancer, Multiome Sequencing Data

  Multiome sequencing of patient tissue and patient derived organoids in colon cancer

  Dataset EGAD00001015504

• OurHealth - Cardiovascular Disease in South Asians

  The OurHealth Study aims to build a biobank comprised of South Asian samples from participants residing in the United States. Primary objectives are to (1) identify genetic and non-genetic drivers of cardiometabolic disease in South Asians, (2) engage participants and researchers in scientific advances and research opportunities to accelerate discovery, and (3) assess the impact of returning polygenic risk scores for cardiovascular-related health conditions. Participants use a web-based platform to complete electronic informed consent, and contribute data via (1) online health surveys, (2) mailed saliva biospecimens for sequencing, and (3) optional electronic health record sharing. Surveys capture medical history, medication data, lifestyle factors, family history, mental health history, and detailed information about cultural and ancestral background. Biospecimens, procured via saliva self-collection kits, undergo DNA isolation and are sequenced using the "blended genome exome" (BGE) method, which consists of sequencing on the NovaSeqX 10B Flowcell followed by Dynamic Read Analysis for GENomics (DRAGEN) analysis for alignment to GRCh38, mapping, and variant calling. BGE uses low-coverage whole genome sequencing (lcWGS) (2-3x) combined with deep-coverage exome sequencing (30-40x), improving on SNP arrays for common variant imputation across European and non-European populations while also capturing rare coding variants. Relative to array genotyping, coverage, genotyping breadth, imputation generalizability, and cost are more optimal.BGE requires imputation for which the NHLBI TOPMed reference panel was used, and GLIMPSE2 was used for imputation emitting genotyping dosages (i.e., 0-2 multimodal continuous). Quality control (QC) included the following procedures. Sample QC excluded those with mean coverage 3% contamination from FREEMIX/VerifyBamID, sex aneuploidy and genotype/phenotype sex-mismatch due to potential phenotyping errors, fingerprinting discordance, and sample metric-level outliers were ancestry-aware, given expected distribution differences. Variant QC metrics including allele frequencies, imputation INFO scores, and Hardy-Weinberg Equilibrium (HWE) p-values are provided with the data; the genotype files provided are not filtered.

  Study phs003821

• Reduced Representation Bisulfite Sequencing (RRBS) in various tissues to discover DNA methylation markers for the diagnosis of breast and ovarian cancer.

  Despite a myriad of attempts in the last three decades to diagnose ovarian cancer (OC) earlier, this clinical aim still remains a significant challenge. In addition, monitoring treatment and early detection of fatal breast cancer (BC) remains a major unmet need. Aberrant methylation patterns of linked CpGs analyzed in DNA fragments shed by cancers into the bloodstream (i.e. cell-free DNA) can provide highly specific signals indicating cancer presence.In order to discover the most relevant CpG regions, we used RRBS and analysed several tissue samples: 11 prospectively collected invasive epithelial ovarian cancer samples (high grade serous n=8, low grade serous n=1, endometrioid n=1, mucinous n=1, mean age = 54.7 years), 8 prospectively collected invasive ductal breast cancer samples (2/8 triple negative; mean age = 56.6 years), one benign tumor (papillary serous cystadenoma, age = 86 years), 18 non-neoplastic tissue samples (breast n=7 and adnexal n=11, mean age = 60.2 years), two non-neoplastic endometrial tissues (mean age = 68 years) and twenty three white blood cell samples (mean age = 57.8 years) were assessed by RRBS. Genome wide methylation analysis was performed by Reduced Representation Bisulfite Sequencing (RRBS) at GATC Biotech. DNA was digested with MspI followed by size selection of the library, providing enhanced coverage for the CpG-rich regions. The digested DNA was adapter ligated, bisulfite modified and PCR amplified. The libraries were sequenced on Illumina’s HiSeq 2500. Analysis of the first samples sequenced with 100bp paired-end mode showed that the library insert size was small. Therefore, the remaining samples were sequenced with 50 bp paired-end mode. Using Genedata Expressionist® for Genomic Profiling v9.1, we established a bioinformatics pipeline for the detection of cancer specific differentially methylated regions (DMRs). The most promising DMRs were taken forward for the development and validation of serum based clinical assays.

  Study EGAS00001002609

• Genomic and Transcriptomic Landscape of Fibrolamellar Hepatocellular Carcinoma

  Fibrolamellar hepatocellular carcinoma (FL-HCC) is a rare liver tumor primarily affecting adolescents and young adults. Little is known of the molecular pathogenesis. To characterize the disease we performed RNA sequencing and whole genome sequencing on FL-HCC tumors and adjacent normal tissue. The results demonstrate few consistent differences on the chromosomal level and many hundreds of alterations in the expression of RNA transcripts.

  Study phs000709

• Studies of a Targeted Risk Reduction Intervention through Defined Exercise (STRRIDE)

  The STRRIDE study is the combination of three interventional trials to evaluate dose and intensity of physical activity on cardiometabolic health. The three component studies are Peripheral Effects of Exercise on Cardiovascular Health (STRRIDE I, ClinicalTrials.gov Identifier: NCT00200993), Effects of Resistence and Aerobic Exercise on Cardiovascular Health (STRRIDE II, ClinicalTrials.gov Identifier: NCT00275145) and Exercise Dose-Response Effects in Prediabetes (STRRIDE-PD, ClinicalTrials.gov Identifier: NCT00962962).

  Study phs001855

• Comprehensive Genomic Characterization of Acral Melanoma

  In this study, we performed paired tumor/normal long insert whole genome and exome sequencing and tumor RNA sequencing on primary or metastatic acral melanoma tumors collected from 34 patients. Patients were enrolled from either Vanderbilt University or the Memorial Sloan-Kettering Cancer Center. We report an integrated analysis of DNA and RNA sequencing data to describe genomic and transcriptomic characteristics of acral melanoma.

  Study phs001036

• Million Veteran Program (MVP) Summary Results from Non-Sensitive Omics Studies

  MVP is an ongoing prospective cohort study and mega‐biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans. This is the accession to hold publicly available results. Results from sensitive phenotypes or MVP population subsets can be found at accession phs001672 and will require an application for access.

  Study phs002453

• The Influence of Gut Microbiota on the Speciation and Toxicity of Mercury During Pregnancy

  There are few studies that have characterized maternal gut microbiota and fetal methylmercury exposure, yet microbes likely modulate this relationship. The primary objective of our pilot study was to determine associations between gut microbial taxa and mercury concentrations in multiple biomarkers (stool, hair, and cord blood). Our secondary objective was to determine the contribution of gut microbial mercury methylation to stool methylmercury.

  Study phs000970

• Nanopore cDNA Sequencing of Chronic Lymphocytic Leukemia

  While splicing changes caused by somatic mutations in SF3B1 are known, identifying full-length isoform changes may better elucidate the functional consequences of these mutations. We have performed nanopore sequencing of full-length cDNA from CLL samples with and without SF3B1 mutation, as well as normal B cell samples. With long reads, we analyzed alternative splicing patterns associated with SF3B1 mutation at an isoform-level.

  Study phs001959

• CALGB/SWOG 80405: Genome-Wide Association Study of Patients with Advanced or Metastatic Colorectal Cancer Treated with First-Line Chemotherapy Combined with Cetuximab and/or Bevacizumab

  CALGB/SWOG 80405 (NCT00265850) was a randomized phase III study of bevacizumab, cetuximab, or the combination of these two monoclonal antibodies, in addition to systemic chemotherapy for patients with untreated metastatic adenocarcinoma of the colon or rectum. We prospectively collected germline DNA and conducted genome-wide association studies using clinical outcomes and molecular features.

  Study phs003428

• DDX50 Cooperates With STAU1 to Effect Stabilization of Pro-Differentiation RNAs

  This study was undertaken to determine the role of DDX50 in epidermal homeostasis. Primary neonatal foreskin keratinocytes were obtained from discarded surgical samples at a California hospital. Samples were anonymous and not selected. DDX50, which was associated with STAU1, was found to promote epidermal differentiation and transcript stability using the methods of RNA-seq, CLIP-seq and DMS-MaP-seq.

  Study phs003766

• Luminal progenitor cell line iHBEC(CD117)

  Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions. After culturing the cells for more than 60 passages, cells were subjected to scRNA-seq as well as bulk RNA sequencing of two subpopulations (CD271+ and CD271-).

  Dataset EGAD50000000723

• Targeted long-read snIso-Seq of the human brain in neurodegenerative diseases

  Nuclei were extracted from postmortem human brain, and cDNA libraries were generated using the 10X Genomics 3' v3.1 kit. Prior to fragmentation, 75% of the library was reserved for long-read sequencing. This unfragmented library was used for target enrichment with a custom 50 gene probe panel from Twist Biosciences. The resulting amplified cDNA libraries were sequenced on a Sequel II. The files provided have undergone CCS generation, and we recommend following the guidelines in https://isoseq.how/ for further analysis starting with removal of primers using lima. The primer sequences that should be supplied are the Read 1 and TSO primers from the 10X Genomics kit.

  Dataset EGAD50000000179

• Replication data for RNA-SEQUENCING: A RELIABLE TOOL TO UNVEIL TRANSCRIPTIONAL LANDSCAPE OF PAEDIATRIC B-OTHER ACUTE LYMPHOBLASTIC LEUKAEMIA

  This dataset contains the raw data of the RNA-seq experiments described in the paper "RNA-Sequencing: a reliable tool to unveil transcriptional landscape of pediatric B-other acute lymphoblastic leukemia" It contains the raw data from 60 pediatric patients diagnosed with B cell progenitor acute lymphoblastic leukemia lacking the main genetic alterations. RNA material was extracted from bone marrow or periphereal blood and RNA libraries were prepared using Illumina® TruSeq™ stranded mRNA kit following manufacturer's instructions and were sequenced in a NextSeq 550 using a v2 HighOutput 150 cycle kit 2x75bp. Funding: Instituto de Salud Carlos III (ISCIII), PI21/00213 

  Dataset EGAD50000000981

• LuCaP cell line ChIP-seq

  ChIP-seq of 2 LuCaP cell lines with different factors. LuCaP cell line 189.4 was ChIP-sequenced for 6 factors with different conditions as well as the input DNA (n=31 in total). LuCaP 189.4 ChIP-sequence experiments include; 3 H3K27ac/DMSO, 3 H3K27ac/vorinostat, 3 H3K27ac/dexamethasone, 3 H3K27ac/dexamethasone/vorinostat, 3 GR dexamethasone, 3 GR dexamethasone/vorinostat, 3 HDAC3/DMSO, 3 AR, 3 FOXA1, 3 H3K27ac and 1 input sample. LuCaP 35 ChIP-sequence experiments as well as input include (n=10 in total); 3 H3K27ac, 3 AR, 3 FOXA1 and 1 input sample. All 41 samples were sequenced using paired-end reads on Illumina NovaSeq 6000. Each sample has 2 fastq files, one for the forward and reverse read, respectively.

  Dataset EGAD50000001345

• Human Cancer-Targeted Immunity via Transgenic Hematopoietic Stem Cell Progeny

  Analysis of a patient biopsy from the clinical trial (NCT03240861), a first-in-human study of transgenic NY-ESO-1 TCR- T cells and NY-ESO-1 TCR+ sr39tk autologous hematopoietic stem cells tandem therapy for solid tumors after myeloablative conditioning chemotherapy with busulfan and fludarabine. Single-cell RNAseq and single-cell ATACseq analysis from peripheral blood mononuclear cells obtained from subject NYSCT-03.

  Study phs003898

• Mutational signatures in normal tissues of patients treated with clinical stage G-quadruplex binder CX5461

  Drug induced photoreactions following exposure to UVA have been documented for several therapeutic compound classes, including psoralens and fluoroquinolones. We used deep (~80X) whole genome sequencing to examine the mutagenic spectrum of CX5461, quinolone-derived small molecule, in normal tissues of cancer patients undergoing treatment. We compared the distribution of somatic base substitutions and short indels from skin biopsies taken from non-sun exposed areas pre and post CX5461 exposure of patients. To further characterize the mutational pattern of CX5461 photoreactivity, we compared mutational profiles of human retinal pigment epithelial cells exposed to UVA, CX5461, or a combination of both UV and CX5461.

  Dataset EGAD50000001640

• T cell and Antibody Responses in Rituximab-Treated Lymphoma Patients After SARS-CoV-2 Vaccination

  This dataset contains T cell receptor (TCR) sequencing data from 51 RNA samples, each processed into three independent libraries (tot 153 FASTQ files). Sequencing was performed on an Illumina NextSeq 500 platform using the NextSeq 500/550 Mid Output Kit v2.5 (300 Cycles), generating paired-end FASTQ files with dual 10 bp barcodes and 5% PhiX as internal control. Libraries were quantified with the Qubit HS dsDNA kit and assessed for fragment size distribution using the Agilent Tapestation D1000 system before isochoric pooling to 4 nM and sequencing in two independent runs. The resulting dataset enables analysis of TCR β-chain CDR3 sequences for clonal expansion and diversity studies.

  Dataset EGAD50000001714

• Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

  This dataset includes FASTQ files of single-nucleus RNA sequencing of cryopreserved kidney biopsy cores from adult patients with diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). A total of 120,751 high-quality nuclei were identified, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs). In addition to the raw FASTQ files, the dataset includes processed data files from all 25 samples, generated using Seurat in R: barcode files, features, count matrices, and associated metadata. Details regarding the bioinformatics pipeline can be found at https://github.com/lambrechtslab/FSGS_Deleersnijder_et_al

  Dataset EGAD50000001557

• scRNAseq - Notch Signaling Maintains a Progenitor-Like Subclass of Hepatocellular Carcinoma

  To clarify the cellular composition and the mechanism of efficacy following JAG1/NOTCH2 inhibition, we performed single-cell sequencing of LIV78 tumors isolated from control animals or following inhibition of JAG1 or NOTCH2. The results suggest that sensitive tumors consist of heterogeneous populations of cells in distinct transcriptional states and that Notch signals emerge from ligand-receptor co-expressing cells.

  Study EGAS50000000517

• Excised DNA Circles from V(D)J Recombination Promote Relapsed Leukaemia

  In this study, we show that ESCs replicate and persist through many cell generations. High ESC copies at diagnosis of BCP-ALL strongly correlate with subsequent relapse. These data provide the first demonstration that the V(D)J recombination by-product, when replicated to elevated levels, potently associates with the V(D)J recombinase to cause adverse disease outcomes.

  Study EGAS50000001043

• Excised DNA Circles from V(D)J Recombination Promote Relapsed Leukaemia

  In this study, we show that ESCs replicate and persist through many cell generations. High ESC copies at diagnosis of BCP-ALL strongly correlate with subsequent relapse. These data provide the first demonstration that the V(D)J recombination by-product, when replicated to elevated levels, potently associates with the V(D)J recombinase to cause adverse disease outcomes.

  Study EGAS50000000407

• Data access to Small RNA-Seq of MicroRNA's in Tear EV's of Ushers Syndrome patients

  Via this DAC you can get access to Small RNA-Seq dataset of MicroRNA's in Tear EV's of Ushers Syndrome patients. The study involved genetically confirmed USH1B patients and their healthy relatives, with additional fibroblast samples from Spanish collaborators, to ensure a robust comparison of small non-coding RNAs (sncRNAs). Tear and blood samples were collected using non-invasive methods, and extracellular vesicles (EVs) were isolated from both tears and hiPSC-derived retinal pigment epithelium (RPE) cells. RNA was extracted from these EVs and assessed for quality before preparing libraries using the TruSeq Small RNA Library Preparation Kit. Sequencing was performed on the Illumina NextSeq 2000 platform, generating data for comparative analysis of sncRNA profiles between patients and controls.

  Dac EGAC50000000711

• Canadian prostate cancer samples (CPC-GENE) for PanProstate study

  CPC-GENE has sequenced the genomes of 350 intermediate risk prostate cancers to identify genetic signatures that differ in cancers that responded well to treatment compared with those that did not. CPC-GENE also has sequenced multiple regions of prostate cancer from the same gland to determine if and how the genetic make-up of prostate cancer varies within an individual man’s prostate

  Study EGAS00001003037

• scCRISPRi/a-seq Control and IFN treated iPS derived human GPC/OPCs

  Datasets consists of 2 batches of human glial progenitors (iPS), cells were sequenced as controls and IFN treated. Using the 10Genomics platform from the samples 2 libraries were built forgene expression libraries (scRNA-seq) and captured guides sequencing library (gRNA) on a set of Multiple Sclerosis associated SNPs. Batch one includes KRAB and P300 perturbed cells in 2 rounds sequenced RNA libraries for Ctrl and IFN and 1 round of capture guides for Ctrl and IFN. Batch 2 includes 1 round of both RNA expresison library and captures guides for KRAB and P300 perturbations in Ctrl and IFN treated cells.

  Dataset EGAD50000002053

• Comprehensive molecular profiling for breast cancer patients and high-risk individuals.

  Although germ-line mutations in BRCA1 and BRCA2 gene are responsible for familial breast and ovarian cancer, the detailed mechanism of tumorigenesis is yet unknown. Here, we performed next-generation sequencing to determine the genomic profiles of familial breast cancer tumorigenesis. Target-capture sequencing of fresh-frozen or formalin-fixed-paraffin-embedded (FFPE) samples of breast cancer or normal breast tissue were performed.

  Study JGAS000368

• Molecular investigation of BCC HHI-ICI combination therapy

  We collected skin biopsies and PBMCs of patients with advanced BCC who underwent HHI-ICI combination therapy. We analyzed the skin biopsies with STx and the PBMCs with scRNA-seq to characterize the response of the immune cells, tumor cells and the tumor microenvironment to this therapy. We were interested in immune activation upon HHI and how that synergises with subsequent ICI.

  Study EGAS50000001481

• RNA-seq of STIC lesions and adjacent normal samples

  In this study, we characterize premalignant lesions of the fallopian tube (serous tubal intraepithelial carcinomas) to explore the earliest events of tumorigenesis following mutation of the TP53 tumor suppressor gene. We conduct laser capture microdissection to isolate premalignant cells from adjacent normal cells, and subject isolated tissues to RNA-seq. Our findings reveal the earliest transcriptional changes established during premalignancy within the fallopian tube.

  Study EGAS50000000200

• Whole-exome sequencing performed on a patient with chronic myelomonocytic leukemia and B cell acute lymphoblastic leukemia

  We studied the rare case of a patient who underwent transformation of myelodysplastic syndrome to chronic myelomonocytic leukemia and B cell acute lymphoblastic leukemia. We used fluorescence-activated cell sorting and whole-exome sequencing to identify driver mutations in the various clones. This allowed us to propose a model of branching clonal evolution with a possible germline predisposition to cancer.

  Study EGAS00001005117

• Myelodysplastic_Syndrome_Exome_Sequnecing

  Cancer is driven by mutation. Illumina GA massively parallel sequencing technology will be applied to Agilent exome hybridisation capture libraries and total genomic paired-end libraries. Bespoke algorithms are being developed to identify the somatically acquired structural variants, point mutations, insertions and deletions in these samples. This project will give unprecedented insights into mutational processes, cellular repair pathways and gene networks associated with Myelodysplastic Syndrome development.

  Study EGAS00001000089

• Genetic_screening__of_GPI_anchor_protein_synthesis__

  This study will analyse the guide sequence which were used for making mutations in the Cas9-expressing cells. We used GeCKO v2 library which were released by Feng Zhang, 2014. 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/

  Study EGAS00001001256

• Congenital_anosmia_2

  Congenital anosmias can be complete (the lack of a sense of smell) or specific (the inability to detect specific smells). Here we obtained genomic DNA from families with multiple individuals with anosmia, suggesting they are congenital. These include those inherited in a manner consistent with dominant and recessive alleles. We have sequenced the exomes of both affected and unaffected family members on the Illumina platform.

  Study EGAS00001001429

• Transcriptomes_of_human_lymphocytes

  In this study we will compare the single cell transcriptomes of immune cells from asthmatics responding to steroids, those refractory to steroids, and a control population.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/

  Study EGAS00001001755

• APCDR AGV Project: WGS of South African Zulu

  The African Genome Variation Project (AGVP) provides a resource to help design, implement and interpret genomic studies in sub-Saharan Africa (SSA) and worldwide. The AGVP represents dense genotypes from 1,481 and whole genome sequences (WGS) from 320 individuals across SSA. As part of the AGVP we sequenced the genome of 100 unrelated Zulu from Durban area to about 4x depth.

  Study EGAS00001000286

• De_novo_mutations_in_cell_free_foetal_DNA__cffDNA_

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women.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/

  Study EGAS00001000322

• APCDR AGV Project: WGS of an Ugandan population

  The African Genome Variation Project (AGVP) provides a resource to help design, implement and interpret genomic studies in sub-Saharan Africa (SSA) and worldwide. The AGVP represents dense genotypes from 1,481 and whole genome sequences (WGS) from 320 individuals across SSA. As part of the AGVP we sequenced the genome of 100 unrelated Baganda from rural Uganda to about 4x depth.

  Study EGAS00001000363

• Whole-exome sequencing of extranodal NK/T cell lymphoma

  Extranodal NK/T cell lymphoma (ENKTCL) is an aggressive Epstein-Barr virus-associated T/NK neoplasm that predominantly affects Asians. To explore the causative somatic events, we conducted a comprehensive genetic analysis of 19 ENKTCL patients including whole-exome sequencing (N = 16). Commonly deregulated gene pathways in ENKTCL included epigenetic modifiers followed by human leukocyte antigen (HLA) and related genes and JAK-STAT pathway.

  Study EGAS00001004357

• Analysis of transcriptomic profiles from affected and recovered muscle biopsies from children with reversible infantile respiratory chain deficiency.

  All patients carry mitochondrial mutation m.14674T>C but not must also carry mutations in related genes such as TRMU and EARS2. Analysis compares muslce biopsies of affected patients to controls, a patient after recovery to themselves during the the disease phase, and compared patients with additional EARS2 mutations to patients without pathogenic EARS2 mutations.

  Study EGAS00001004647

• Whole transcriptome and exome sequencing of childhood ALL

  Gene fusion is a major class of genomic abnormalities in childhood acute lymphoblastic leukemia (ALL) and sentinel chromosomal rearrangements involving EP300 and CREBBP may cause global epigenetic deregulation during leukemogenesis with potentials for therapeutic targeting. This dataset includes whole transcriptome sequencing of 231 children with acute lymphoblastic leukemia from a Singapore-Malaysia frontline clinical treatment protocol.

  Study EGAS00001001858

• Cylindromas_sun_protected_and_exposed

  The project aims to look at mutational signatures in a rare inherited skin tumour syndrome called CYLD cutaneous syndrome. These patients develop multiple skin tumours that are seen at sun exposed and sun protected sites. We plan to carry out WGS on carefully curated tumours from such patients. We then plan to analyse this data for mutational signatures, comparing this between sun exposed and sun protected sites.

  Study EGAS00001002521

• Misoprostol-induced high fever GWAS study

  Genome-wide association (GWAS) meta-analysis study of misoprostol-induced fever was conducted on two South American cohorts (Argentina and Ecuador). DNA was collected from blood of women who were screened for postpartum haemorrhage (PPH) and administered misoprostol were included in the study. Genotypes were acquired from the Global Screening Array (Illumina). Meta-analysis of these cohorts was completed using METAL software.

  Study EGAS00001005455

• Exome sequencing of paired primary tumor and metastatic breast cancer

  Prognosis evaluation of advanced breast cancer and therapeutic strategy are mostly based on clinical features of advanced disease and molecular profiling of the primary tumor. Very few studies have evaluated the impact of a prospective documentation of metastatic subtyping. The genomic landscape of metastatic breast cancer has mostly been described in very advanced, pretreated disease, limiting its transferability to clinical use.

  Study EGAS00001004578

• NIHR BioResource Common Disease Patients 2016

  NIHR BioResource Common Disease Patients 2016. The dataset includes 13489 samples from blood donors, they were not screened for any particular disease, and therefore they are representative of the general population. Genomic data includes 845487 snps collected using the UK BioBank V1 Affymetrix array. Phenotypic data includes gender, age, ethnicity and disease. According to our internal quality check there are 81 duplicates in this dataset.

  Study EGAS00001004870

• Whole genome landscape of 25 metastatic cutaneous squamous cell carcinoma cSCC patients

  whole genome sequencing on lymph node metastases and blood DNA from 25 cSCC patients with regional metastases of the head and neck. We designed a multifaceted computational analysis at the whole genome level to provide a more comprehensive perspective of the genomic landscape of metastatic cSCC. This study contains the majority of 15 samples which are previously submitted in EGAC00001001100.

  Study EGAS00001006378

• SDH_deficient_renal_tumours___WGS_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004102

• Gene expression profiles of single disseminated breast cancer cells

  A set of 56 EpCAM-positive cells derived from bone marrow aspirates of breast cancer patients or patients without a cancererous disease (30 cells from 21 M0-stage and 11 cells from five M1-stage breast cancer patients, 15 cells from seven non-cancer patients serving as controls). EpCAM-positive cells from breast cancer patients were considered disseminated tumor cells as they harbored copy number alterations and showed high expression of the epithelial marker EpCAM and the mammary luminal progenitor marker KIT in comparison to EpCAM-positive bone marrow cells from non-cancer patients. Paired-end RNA-Sequencing of the samples was performed on Illumina NovaSeq6000, raw data are provided in the Fastq format.

  Dataset EGAD00001006359

• Reconstruction of complex rearrangement patterns causing the initiation of clear cell renal cell carcinoma.

  The genomic hallmark of clear cell renal cell carcinoma is the loss of the short arm of chromosome three. This appears to be the earliest genomic event in the formation of these cancers. Often chromosome 3 is lost at the same time as part of chromosome 5 is duplicated via an unbalanced translocation, often with features consistent with focal chromothripsis. In this study, we sought to reconstruct the chromothriptic event that underlies the initiation of kidney cancer. We used long read sequencing (promethION, Oxford Nanopore Technologies) of patient tumour-derived DNA to elucidate how a single cell division error can generate cancer genome complexity.

  Dataset EGAD00001005495

• Benchmarking dataset for ProSolo, a probabilistic single nucleotide caller for single cell DNA sequencing data

  This is the dataset used in the benchmarking of ProSolo, a new probabilistic single nucleotide variant caller for single cell DNA sequencing data that provides control over the false discovery rate of different single cell events at genomic sites (e.g. alternative allele presence or allele dropout). It provides the whole exome sequencing data used in assessing ProSolo's performance that is not available elsewhere, namely bulk whole exome sequencing data of a patient with a constitutional mismatch repair defect (MSH6-) and their parents and siblings, a bulk whole exome sample of granulocytes from that patient and 5 single granulocytes whole exome sequenced after whole genome amplification.

  Dataset EGAD00001005929

• T-VEC CBCL scRNA

  We are presenting raw and processed data of our study where we analyze fine-needle aspirate (FNA) samples of primary cutaneous B-cell lymphoma patients undergoing oncolytic virotherapy (https://clinicaltrials.gov/ct2/show/NCT03458117). We are uploading single cell RNA-sequencing and immune repertoire profiling data of 29 FNA samples from four pCBCL patients. The four patients have three different subtypes of primary cutaneous B-cell lymphoma: pCDLBCL-LT, pCFCL and pCMZL. The samples are taken at different time points following T-VEC injection (from baseline up to 91 days after injection). We are uploading the sequences in BAM format and the outputs of the cellranger pipeline (count matrices and filtered VDJ contigs) in CSV format.

  Dataset EGAD00001006829

• sWGS on cfDNA and matching tumor DNA in pediatric cancer

  This dataset contains shallow whole genome sequencing data from paired cfDNA - tumor DNA samples of various pediatric cancer entities (total 215 samples). Files are provided in fastq format. Samples were sequenced on an Ion Proton sequencer (Thermo Fisher Scientific) or a Hiseq3000 (Illumina). Data analysis is available at https://github.com/rmvpaeme/sWGS_pediatric_cancer.

  Dataset EGAD00001007508

• Genomic characterisation of SDH deficient renal cell carcinoma - RNA

  SDH deficient renal cell carcinomas are a rare and recently defined subtype of kidney cancer, often associated with an inherited mutation in one of the SDH gene subunits. This dataset sought to understand the genomic events that underpin tumour formation, from putative cell of origin, characterisation of the tumour microenvironment, to the genomic evolution of these rare tumours. We performed whole genome and RNA sequencing of 4 patients with SDH deficient renal cell carcinomas, including one patient who had an additional paraganglioma. An addition patient in this cohort had the initial diagnosis revised to a clear cell renal cell carcinoma.

  Dataset EGAD00001008470

• Unravelling the contribution of HIF pathway and its therapeutic potential in human AML leukemia-initiating cells

  We performed single cell RNA sequencing (scRNA-seq) from bone marrow on 11 pediatric (0-14 years-old) and adolescent and young adult (AYA) (15-39 years-old) de novo AML samples (Dx) (4 inv(16), 3 t(8;21) and 4 rMLL). In addition, for some patients also relapse sample was sequenced (2 inv(16), 2 t(8;21) and 3 rMLL). Cells were sorted into CD34+/CD38- and CD34-/CD38+ and sequenced separately.

  Dataset EGAD00001008514

• Pharmacogenomic profiling reveals molecular features of chemotherapy resistance in IDH wild type primary glioblastoma

  We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy.

  Dataset EGAD00001010156

• Longitudinal RNA-seq datasets from patients after abdominal surgery

  This dataset consists of RNA-seq data of 126 whole-blood samples derived from patients after abdominal surgery. Total-RNA collected preoperatively and at 3-time points postoperatively (2-6, 24 and 48hrs) were analysed using RNA-sequencing. RNA was collected in PAXGene (Qiagen) tubes and extracted using the PAXGene RNA extraction kit, with a DNase step to remove contaminating DNA. Globin and ribosomal RNA were removed via a Ribo-zero kit (Illumina) and library preparation was carried out using the TruSeq Stranded Total RNA Library Prep Kit (Illumina). Next generation sequencing was performed on the NovaSeq sequencing platform (Illumina) at the Wellcome Centre for Human Genetics (WCHG) in Oxford.

  Dataset EGAD00001011102

• A standardised framework for robust fragmentomic feature extraction from cell-free DNA sequencing data

  Fragmentomic features of cell-free DNA represent promising non-invasive biomarkers for cancer diagnosis. However, a lack of systematic evaluation of biases in feature quantification has hindered the adoption of such applications. We compared features derived from whole-genome sequencing of ten healthy donors using nine library kits and ten data-processing routes, and validated them in 1,182 plasma samples from published studies. Our results clarify the variations resulting from library preparation and feature quantification methods. We designed the Trim Align Pipeline and the cfDNAPro R package as unified interfaces for data pre-processing, feature extraction, and visualisation, aiming to standardise multimodal feature engineering and integration for machine learning.

  Dataset EGAD00001015535

• Whole Genome, RNA, and ChIP Sequencing of matched brain tumor-normal pairs (ICGC)

  Whole Genome Seq: Illumina HiSeq sequence data (with >30x coverage) were aligned to the hg19 human reference genome assembly using BWA (Li and Durbin, 2009);duplicate reads were removed from the final BAM file. No realignment or recalibration was performed. Paired-end RNA sequencing reads were mapped to the hg19 assembly of the human reference genome using BWA.Each ChIP-seq library was sequenced with two complete lanes on the Illumina HiSeq 2500 in the 101-bases paired-end rapid mode and aligned to hg19 using bwa.This resulted in the following coverage values (genome-wide, after deduplication, including all uniquely mapping reads):GBM103 macroH2A1: 17x H3K36me3: 20xMB59 macroH2A1: 11x H3K36me3: 11x

  Dataset EGAD00001000664

• European Prospective Investigation into Cancer and Nutrition BAMs

  516 DNA samples were collected from individuals upon enrollment into the European Prospective Investigation into Cancer and Nutrition study between 1993 and 1998 across 17 different centers. 126bp pair-end reads sequencing data from the Illumina platform were converted to fastq format, the 2bp molecular barcode information at each read of the pair was trimmed and was written in the reads name. The Thymine nucleotide required for ligation was removed from the sequences. Burroughs-Wheeler Aligner (BWA-mem) was used for alignment of the processed fastq files to the reference hg19 genome, following indel-re-alignment using GATK. An in-house algorithm was written to collapse read families that share the same molecular barcode sequence

  Dataset EGAD00001003583

• Tumor-derived cell lines as pharmacogenomic models to predict therapeutic vulnerabilities in hepatocellular carcinoma

  Hepatocellular carcinoma (HCC) is a heterogeneous aggressive malignancy with low efficacy of current therapies at advanced stages. We integrated molecular and pharmacological profiling of a large panel of liver cancer cell lines (LCCL) to assess their clinical relevance as HCC preclinical models and identify new effective therapies and biomarkers of response. Here, we performed multi-omic analysis including whole-exome, RNA and microRNA sequencing in a series 34 LCCL. Molecular profiles of LCCL and primary HCC were compared and we searched for molecular features associated with drug response. Our panel of LCCL faithfully recapitulated the most aggressive molecular “proliferation class” of HCC.

  Dataset EGAD00001004938

• DNA repair in BLM deficient hiPSCs

  We are aiming to investigate repair of a double strand break (DSB) within the genome in the presence and absence of the BLOOM protein. Zinc Finger Nucleases introduce DSBs at specified loci within the genome. Using sequencing we will assess the size of the deletion following repair. Protocol 1. Transfect normal and BLOOM deficient human iPS cells with ZFNs, using AMXA 2. Harvest cells after 5 days 3. Perform column extraction of DNA 4. PCR-amplify the ZFN region 5. Sequence and analyse repair of the DSB 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 EGAD00001000819

• GoT2D: Genetics of Type 2 Diabetes, a study of the the genetic architecture of type 2 diabetes

  The GoT2D study includes ~2800 samples, half T2D cases and half T2D controls, of Northern European ancestry sequenced over 3 three technologies: deep whole exome sequencing, low-pass (4x) whole genome sequencing, and OMNI 2.5M genotyping. Samples were ascertained to be phenotypically "extreme" (e.g. leaner, younger cases and older, more obese controls). Genotypes (SNVs, INDELs, and SVs) were called separately for each technology and then integrated via genotype refinement into a single phased reference panel; samples and variants were then excluded based on QC procedures described in Fuchsberger et al. Please note that 2 of the samples in the GoT2D vcf do not have phenotype data.

  Dataset EGAD00001002247

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002698

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Pharmacokinetic Polymorphisms in Japanese General Population

  This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfAnalysis of 165 pharmacokinetic-related gene polymorphisms (the number of polymorphisms may increase) using DNA derived from the blood of approximately 1,000 Japanese general populations. Tokai University School of Medicine Molecular Life Sciences 2 Isogo Lab has been trying to find new genes which contribute to the development of multiple diseases and to develop new methods for human genome diversity analysis that will lead to the development of technology for disease screening by finding genes related to diseases and incorporating gene analysis technology. Using this method, we are trying to clarify the relationship between the characteristics of rheumatoid arthritis and psoriasis vulgaris and genes to seek effective treatments and prevention methods. Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data. For questions about availability contact help@lists.anvilproject.org.

  Study phs002985

• DAC Portal documentation

  DAC Portal Welcome to the DAC Portal documentation! If you are involved in governance or legal aspects, technical or operational aspects, or serving as a data steward, this page will be helpful for you. By exploring these materials, you can define your own Data Access Committee (DAC) and policies, understand the minimal requirements for a DAC and a policy object, and comprehend how the EGA data access requests are managed. DAC Portal Index Setting up your account DACs and Policies Pending Request table Manage Data Requests History page Audit your DACs, policies, and datasets Deprecation User Preferences DAC API - A programmatic approach Setting up your account Register yourself as an EGA user. The Helpdesk team will validate your account (this could take up to 48 hours). After validation, you will receive an email with a link to verify your email - Make sure you click on the link to verify your account! If you don’t receive the email, please check your spam folder. Once your account is active you can login to the DAC Portal. We recommend you to check out the Take The Tour! DACs and Policies Create a DAC Click on Create a DAC Add the title and description to your DAC. Once ready, click on the ‘Create’ button. You will have to wait until the Helpdesk Team validates the creation of your DAC. Once approved by Helpdesk, your DAC will be assigned with a persistent identifier (EGAC). Edit a DAC Once your DAC is registered and approved, you can edit it and add contacts. Remember, you can add as many contacts as needed. And, you can also remove/add contacts anytime. To add a contact, you must write the username or email of a registered EGA user in the Members field. Once you have typed the whole username or email, a drop-down menu will appear where you can select the contact. Select a contact from the drop-down menu. Make sure you write the full username or email of the contact so it appears as an option. Make sure that you select one main contact. Set up the role you want to grant to the new contact of the DAC. We recommend you to check out the FAQ to learn more about the different roles! After adding all the necessary contacts and assigning roles, click on Update. This will send an email notification to the new DAC member, letting them know about the invitation to managing the DAC. Once they log into the DAC Portal, they will be able to either accept or turn down the invitation. Create a policy First, please note that all information registered in a policy metadata object will be publicly available on the EGA website. For each released dataset, all users will be able to read the policy under the “Data Access” tab. Select Create a Policy from the Policies tab. Select the DAC that you want your policy to depend on. Add the title and terms and conditions for accessing and using your data. If you already have an external website for data access requests, you can add the URL directly here (see example here). You can find a template of a Data Access Agreement (DAA) document in our Policy documentation page. The DAA template is provided for guidance only and should be adapted to suit your own purpose depending on the security policies, terms for publication or embargoes, and restrictions on data use or sharing. You can also add Data Use Ontologies (DUO) to your policy. These DUO codes are used to semantically tag the terms and conditions of using the data linked to the policy (example). For more information, you can refer to the Data Uso Ontology documentation. Once completed, make sure to click the Create button in order to register your policy. A persistent identifier (EGAP) will be assigned automatically. Edit a policy Please, note that you will not be able to edit the policy if it shows in orange. Meaning that you are a member of the DAC linked to that policy. Members don’t have edit rights. Only admins can edit objects. You can check your registered policies on My policies, available at the menu in the top-right corner. Select your policy. It will then display the information of that policy, allowing you to edit the information. Once you are done with the modifications, click Update. Pending Requests Table Table Settings Upon selecting a specific DAC, you will be presented with a customisable table showcasing all pending data access requests. This table allows you to tailor the displayed information according to your preferences by selecting desired columns. Available Columns (Displayed with the Eye Icon): Date: The date when the data access request was submitted. Full Name: Name and surname of the user submitting the request. Email: Email address associated with the user's request. Username: The username linked to the EGA account of the user submitting the request. Organisation: Affiliated organisation of the user submitting the request. Dataset: EGA accession ID for the requested EGA dataset. Dataset Title: Title of the requested dataset. DAC Comment: Space provided for internal comments related to the request. Expiration: Option to specify an expiration date for granted permissions. Check more information on the pending request table here! Table Filters By default, all data access requests are displayed. However, you have the option to apply filters to refine your view. Follow these steps to apply filters: Click on the More button. This action will reveal the different columns available for applying filters. As you select columns, the checked fields will be displayed at the top of the request table. Choose the specific values within the selected columns that you want to filter for. Click the Search button to apply the selected filters. Do you find yourself frequently applying the same filters? You can save multiple combinations of filters for easy access at any time! Here's how: Click the Save button. Provide a descriptive name for the filter combination. Click Save to confirm. To load saved filters, simply select the saved filter from the dropdown menu to apply it automatically. Check more information on filters here! Advanced Search For users requiring more granular control over their data access requests, the DAC Portal offers an Advanced Search feature using JIRA Query Language (JQL). With JQL, you can craft precise and complex queries to filter and retrieve specific data access requests based on various criteria such as date, user details, dataset attributes, and more. Using JQL's flexibility, you can create custom queries to meet your specific needs, allowing for advanced filtering options beyond the standard filters provided. You can find the Advanced Search feature following these steps: Click the … button Select Advanced To view the allowed fields for filtering and explore all available options, simply click on the info icon. Once you have written the filtering values, click the Search button to apply. Check more information on filters here! Manage Data Requests Upon logging into the DAC Portal, you'll notice a sand clock icon next to the DAC ID, indicating the number of pending requests. Click on the DAC to review these requests. Accept requests Click on the right side of the toggle button to grant access to the user. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with granting permissions. Deny requests Click on the left side of the toggle button to deny access to the user. Provide a reason for the denial. Note that the user will receive an email with this reason. Click on the Done button. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with denying permissions. Tips! Apply a filter to view all requests to be managed at once. Use the toggle in the row with column names to grant or deny permissions for multiple requests simultaneously. You can grant and deny permissions in the same action, simplifying the process. The confirmation box will provide a summary of all actions, including grants, denials, DAC comments, and expiration dates. History Page The History page serves as a dedicated space to view information regarding all requests managed by all DAC members. Here, you can review active permissions and revoke them as needed. Go to the History page by clicking on the "HISTORY" button from a DAC page in the DAC Portal. Here are the different row types you may find: Current permissions: row in green with a toggle button to revoke permissions on the right. Approved requests: row in green, with no toggle button. Request denied: row in red with “request denied” on the right. Permission revoked: row in red with “permission revoked” on the right. Distinctions to Note! Between Request Denied and Permission Revoked: Request Denied: Refers to requests that were rejected from the outset, indicating that access to the dataset was never granted. Permission Revoked: Indicates that permissions were previously granted but have since been revoked. Users with permissions revoked have previously accessed the dataset. Between Approved Request and Current Permissions: Approved Request: Represents an entry when a data access request has been approved in the past. Current Permissions: Denotes ongoing permissions where a user has present access to the dataset. An approved request may now appear as Permission Revoked in the present. By observing these different rows, users can gain insight into the complete history of a user's interactions and permissions regarding a dataset over time. To revoke access to a specific user for a dataset, follow these steps: Go to History page Look for the row with the specific permissions. You can use the filters! Click on the toggle button to revoke access. Add a denial reason. Bear in mind that the requester will receive the denial reason! Click on the Apply button. Check more information on the Hisotry page here! Audit your metadata objects In the DAC Portal, you can efficiently manage and audit various metadata objects pertinent to your role as a Data Controller. Upon accessing the DAC Portal, you will encounter three primary tabs on the homepage: DAC: Contains information about Data Access Committees (DACs). Policies: Provides insights into linked policies. Datasets: Displays datasets and relevant details. Within each tab, you'll find a comprehensive list of the objects you manage, these being grouped by type (DAC, Policies, Datasets), as well as by your role (member/admin). Whilst the lists give you a quick look, to check how things are connected, we've added a table at the bottom DACs and policies. DACs Let’s check which policies are linked to a specific DAC: Go to "My DACs." Select a DAC. Click on "EDIT" to see more details. You are now on this page: Scroll down to see the linked policies. Click on “List of linked policies of this DAC” and you will see a list of all policies linked to your selected DAC. Policies Do you want to view a list of datasets connected to a particular policy? Follow the same steps mentioned earlier, but head to the policy tab this time. In the policy tab, you'll find a list of all your policies. Here, you may notice two different icons next to the policy ID (EGAP): DAC Icon (): This represents the DAC. Hover your mouse over the icon to see the DAC ID. Dataset icon (): This indicates datasets falling under that policy. The number next to the icon tells you how many datasets are linked to the policy. For example, if you see "2" next to the icon, it means there are two datasets linked to that policy. If you want to check the linked datasets and their relevant information, simply click on a specific policy. You'll then find the "List of linked datasets of this policy" at the bottom of the page. Datasets Finally, in the dataset tab, by default you will see a list of all the datasets you can manage with all your DACs and policies. Yet, we've included two handy ways to organise them: DAC vs. policy: You can group by datasets, either by DAC or policy. Released vs. unreleased: You can sort out datasets based on their release status. Feel free to experiment with both options! For instance, if you want to see which DACs have unreleased datasets, simply select DAC and unreleased, and you'll get the details you need! Deprecation Do you have a bunch of metadata objects like DACs and policies that you don’t need anymore? This section shows you how to get rid of them! But what does "deprecation" mean for EGA? It's basically changing the status of a metadata object to "deprecated," which means we won't be using it in the future. In simple terms, it's like saying these objects are no longer useful. However, because we believe in making metadata FAIR, once an object has a persistent identifier, we can't just delete it. So, instead of deleting, we deprecate it. Here's a helpful tip! If you want to make a metadata object disappear from the DAC Portal, deprecate it. You won’t see it in the portal anymore! Let’s say you want to deprecate a DAC. Let’s do it! Go to "My DACs." Select a DAC. Click "EDIT" to see more details. You are now in this page: Click on the Deprecate button It will then appear a message. There are two options here: Your DAC is not linked to any policy, hence it’s ready to be deprecated. Click on “Yes. Confirm” to deprecate your DAC object! Your DAC is linked to at least one policy, and you need to either: Deprecate the linked policy first, or Link the policy to a different DAC Now, let’s say you don’t want to get rid of the policy altogether, but you want to change the DAC it’s linked to. Here's how: Go to the policy tab. Find the policy you want to change (for example, EGAP50000000019). Choose a new DAC to link it to. Click on Update. See the Edit Policy section for more details. After ensuring that the DAC we want to deprecate isn’t linked to any policy, return to the "My DACs" section and follow the steps outlined previously. This will lead you to a confirmation message. You can only deprecate DACs and Policies. To deprecate a dataset, please contact our Helpdesk team. Check more information on how deprecation works here! User Preferences We have implemented email notifications in the DAC Portal. Here’s the complete list: DACs: Pending requests Approved by Helpdesk Rejected by Helpdesk DAC Invitation Requesters: Data access request approved Data access request denied Permissions revoked Upcoming expiration date As a DAC member, you will be able to decide whether you want to receive the DAC notifications or not. For that, go to the top-right corner menu, select User Preference. You will be able to decide whether you want to receive notifications for: Approved by Helpdesk Rejected by Helpdesk DAC Invitation For pending requests, you will be able to select how often do you want to receive the notification: Daily Weekly Fortnightly As a DAC member, you are responsible for managing data access requests. Consequently, you will receive notifications for pending requests. If you prefer not to manage these requests, please arrange to be removed as a contact for your DAC. Here's a tip! Do you have a pending request that you don’t want to receive a notification? Add a DAC comment! The EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! DAC API - A programmatic approach In addition to the new DAC Portal, we are excited to announce the release of the DAC API. This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can click the button below. Check out the DAC API specification!

  Documentation access/data-access-committee/dac-portal

• Enhancer Mapping in Chronic Lymphocytic Leukemia

  In this study we profile the epigenomic enhancer landscapes of CLL B cells (CD19+/CD5+) harvested from peripheral blood of patients from our Center. Included are results of ChIPseq profiling using chromatin immunoprecipitation of the enhancer histone mark H3K27ac (acetylated lysine 27 on histone H3), and open chromatin profiles using ATAC-seq (assay for transposase accessible chromatin). These profiles are used to define the global enhancer and super enhancer landscape of CLL B cells, and to derive active transcription factor networks associated with this disease. Also included are H3K27ac ChIP-seq and ATAC-seq datasets for non-CLL B cells obtained from the peripheral blood of normal adult donors.

  Study phs001704

• Coenzyme Q10 (CoQ) in Huntington's Disease (HD) (2CARE)

  This is a multi-center, randomized, double-blind, placebo-controlled trial of CoQ involving 609 ambulatory subjects with HD who are not requiring skilled care or institutionalization. Eligible subjects were randomized to receive either CoQ 2400 mg/day or matching placebo. Subjects were followed prospectively and systematically for 60 months of double-blind observation. The primary outcome variable is a combination of time to death (for subjects who die) and the change from baseline to Month 60 in Total Functional Capacity (TFC) score (for subjects who survive). The primary hypothesis of the study is that chronic treatment of early-stage HD subjects with high-dosage CoQ will slow the progressive functional decline of HD.

  Study phs001065

• NHLBI TOPMed: Rare Variants for Hypertension in Taiwan Chinese (THRV)

  The THRV-TOPMed study consists of three cohorts: The SAPPHIRe Family cohort (N=1,271), TSGH (Tri-Service General Hospital, a hospital-based cohort, N=160), and TCVGH (Taichung Veterans General Hospital, another hospital-based cohort, N=922), all based in Taiwan. 1,271 subjects were previously recruited as part of the NHLBI-sponsored SAPPHIRe Network (which is part of the Family Blood Pressure Program, FBPP). The SAPPHIRe families were recruited to have two or more hypertensive sibs, some families also with one normotensive/hypotensive sib. The two Hospital-based cohorts (TSGH and TCVGH) both recruited unrelated subjects with different recruitment criteria (matched with SAPPHIRe subjects for age, sex, and BMI category).

  Study phs001387

• The Gut Microbiome in Parkinson's Disease

  The uploaded data come from a nested case-control study, with participants with Premotor Parkinson Disease (PPS) as cases. In addition to the PPS cases, the study has three control groups: 1) constipation only controls, defined as those who only reported constipation, but not probable REM sleep behavior disorder (pRBD) or hyposmia; 2) healthy controls  who did not report constipation, pRBD or hyposmia; and 3) patients with recently diagnosed confirmed PD (diagnosed after January 1, 2010).  Participants were contacted between 2016 and 2020 for a set of two stool samples. All participants provided a baseline stool sample and a subset (N = 120) will provide a second stool sample.

  Study phs002193

• Single cell RNAseq 7 days - Calprotectin in vitro effects on human early hematopoiesis

  To explore the effects of calprotectin (CAL) on early hematopoiesis, we incubated CD34+ cells from four healthy donors for 7 days in the presence of stem cell factor (SCF), FLT3-ligand and thrombopoietin (TPO) without and with CAL, interleukin-6 (IL6) and the IL6_CAL combination before collecting cells. We performed the same experiment with CD34+ cells collected from three patients with JAK2-V617F-mediated myelofibrosis (MF). A total of 135,545 cells from healthy donors and 111,725 cells from myelofibrosis patients were analyzed by single-cell RNA sequencing (scRNA-seq) using the 10X Chromium droplet-based platform. Single cell RNAseq 7 days - Normal and tumor samples 4 conditons : -Control - Calprotectin - IL-6 - Calprotectin+IL-6

  Study EGAS50000000455

• Bulk ATACseq 7days - Calprotectin in vitro effects on human early hematopoiesis

  To explore the effects of calprotectin (CAL) on early hematopoiesis, we incubated CD34+ cells from four healthy donors for 7 days in the presence of stem cell factor (SCF), FLT3-ligand and thrombopoietin (TPO) without and with CAL, interleukin-6 (IL6) and the IL6_CAL combination before collecting cells. We performed the same experiment with CD34+ cells collected from three patients with JAK2-V617F-mediated myelofibrosis (MF). A total of 135,545 cells from healthy donors and 111,725 cells from myelofibrosis patients were analyzed by single-cell RNA sequencing (scRNA-seq) using the 10X Chromium droplet-based platform. Bulk ATACseq 7days - Normal and tumor samples 4 conditons : -Control - Calprotectin - IL-6 - Calprotectin+IL-6

  Study EGAS50000000456

• Depth of Response Correlates with Improved Outcomes for Early Interception in a High-Risk Smoldering Multiple Myeloma Clinical Trial Using the Combination of Ixazomib, Lenalidomide, and Dexamethasone

  Early treatment of patients with high-risk smoldering myeloma (HRSMM) has been shown to delay progression to multiple myeloma (MM), but not all patients respond well. Identifying biological predictors of response and resistance to treatment can help optimize treatment selection for patients and improve outcomes. Here, we investigate tumor and immune biomarkers of response to ixazomib, lenalidomide, and dexamethasone treatment (I-PRISM study) that can be measured at diagnosis. We performed single-cell RNA sequencing (scRNAseq), coupled with B cell receptor and T cell receptor sequencing, on CD138+ tumor and CD138- immune cells, respectively, from the bone marrow of 20 patients enrolled in the I-PRISM study.

  Study phs003827

• Comparison of WGBS, EPIC array, EM-seq, and Nanopore sequencing in assessing DNA methylation marks

  Bisulfite sequencing has long been the default method for analyzing methylation marks due to its single base resolution. However, the associated DNA degradation poses a concern for fragmented samples. Although several methods have been proposed to circumvent this issue, there has yet to be a clear consensus on which method is best suited for detecting methylation. We present an overview of the two mostly used and two alternative approaches: whole-genome bisulfite sequencing (WGBS), Illumina methylation microarray (EPIC), Enzymatic Methyl-sequencing (EM-seq) and third-generation sequencing by Oxford Nanopore Technologies (ONT). We evaluated DNA methylation levels in three human genomes derived from tissue, cell line, and whole blood.

  Study EGAS00001008014

• A Cultured Leukemia Stem Cell Model Enables Validation of CDK6 as a Stemness Target Against Acute Myeloid Leukemia

  Acute myeloid leukemia (AML) represents a group of aggressive hematological malignancies, the clinical management of which is made challenging due to the persistence of rare and therapy resistant leukemia stem cells (LSCs) which serve as a source of disease relapse and poor outcomes. There are currently a paucity of methods to reliably enrich and study LSCs, hindering the development of therapies that specifically target LSCs. In this study, we deeply characterize the OCI-AML8227 culture model, which maintains a functional stemness hierarchy originating from its highly primitive CD34⁺CD38⁻ cells, to elucidate LSC biology and uncover LSC-specific therapeutic vulnerabilities. We analyzed both bulk and single-cell proteomics, transcriptomics, and epigenomics to generate a LSC protein-protein interaction network, which was then integrated with an LSC-focused small molecule screen using this model. From these findings, CDK6 was discovered as a therapeutic vulnerability specific to LSCs, which was validated in findings from the BEAT-AML cohort and a patient-derived xenograft (PDX) panel of AML samples through palbociclib treatment. Taken together, our studies validate CDK6 as a druggable vulnerability in LSCs, and authenticate OCI-AML8227 cells as a LSC target discovery engine.

  Dataset EGAD50000001156

• Ultra-deep Error-corrected Sequencing of Peripheral Blood for Clonal Hematopoiesis in Patients Undergoing AAA Surgery

  Patients undergoing elective abdominal aortic aneurysm (AAA) surgery were enrolled to investigate the prevalence and characteristics of clonal hematopoiesis. Peripheral blood was collected at the time of surgical admission using PAXgene DNA tubes. Genomic DNA was extracted and subjected to ultra-deep error-corrected targeted sequencing using a custom gene panel covering recurrent clonal hematopoiesis-associated genes. Sequencing libraries were prepared following established protocols and sequenced on an Illumina NovaSeq X system. The resulting dataset includes paired-end FASTQ files for each participant, enabling high-sensitivity detection of somatic variants down to low variant allele frequencies. This study provides a comprehensive sequencing resource for evaluating clonal hematopoiesis in AAA patients.

  Study JGAS000864

• EGA FUSE Client

  EGA FUSE Client What is EGA FUSE Client? The EGA FUSE Client is a Java Native Runtime (JNR) based Filesystem in Userspace (FUSE) client that allows users to access authorised EGA files by presenting them in a virtual directory. This means that users can use authorised EGA files like regular files without having to download them first. The EGA FUSE Client is a useful tool for researchers who need to access and work with large amounts of EGA data. Why use EGA FUSE Client? The EGA FUSE Client provides several benefits for researchers working with EGA data: Efficient use of storage space: With the EGA FUSE Client, users can access authorised EGA files without having to download them first. This means that users can save storage space on their local machines. Faster access to data: Since users can access authorised EGA files directly through the EGA FUSE Client, they can work with the data more quickly than if they had to download the files first. Simplified workflow: The EGA FUSE Client presents authorised EGA files in a virtual directory, allowing users to work with the files like regular files. This simplifies the workflow for researchers who need to access and work with large amounts of EGA data. Get started with EGA FUSE Client To get started with EGA FUSE Client visit the EGA FUSE Client GitHub repository for more information and installation instructions.

  Documentation access/download/visualisation/fuse-client

• EGA submission account terms

  Submission account terms Each EGA submission account has a dedicated submission box. To ensure continued service to all submitters EGA submission boxes should not exceed 8Tb in size, and cannot exceed 12Tb. Those that are near to or exceeding this value will be monitored on a weekly basis by the helpdesk team and the submitter will be contacted and guidance provided accordingly on completing their metadata registration. You will be able to register your metadata associated with the files in your submission account via EGA Submitter Portal, Webin or the EGA REST API. EGA also requests that metadata is submitted within 60 days of upload data to a submission box. When we detect files that are over 60 days old in a submission box we will notify the submitter requesting that metadata be submitted or the files removed from the submission box. It is important to note that data is not archived at the EGA until the metadata describing the files has been associated and the archival process has completed. It is only when associated metadata has been submitted that the archival process into EGA is fully triggered. EGA removes files from the submission box once they have been successfully archived, so no action is required by a submitter to remove successfully archived files. Files over 90 days old will be deleted from the submission box unless EGA Helpdesk has been contacted and confirmed an exemption with the submitter.

  Documentation submission/terms

• Origins and timing of emerging lesions in advanced renal cell carcinoma

  Renal cell carcinoma (RCC) with venous tumor thrombus (VTT) arising from the primary tumor occurs in ~10% of cases and is thought to represent more advanced disease. RCC with VTT and distant metastasis provides unique opportunities to examine the origins and relative timing of tumor lesion emergence and to identify molecular correlates with disease state. We performed multi-region exome and RNA sequencing analysis of a clinical cohort of 16 RCC patients with VTT, with eight patients also having sequenced metastasis, to examine which genomic alterations, biological pathways, and evolutionary processes contribute to VTT and metastasis, and to ask whether metastasis typically arises directly from VTT or is independent of VTT.

  Study EGAS00001005897

• Time-dependent characterization of CNS response in COVID-19

  Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 primarily affects the respiratory system, but the observation of diverse neurological symptoms indicates that other organs, including the brain, may be involved. The pathophysiological mechanisms of COVID-19-associated effects on the central nervous system (CNS) have become clearer during the past two years. Nevertheless, the precise CNS-specific molecular mechanisms are still elusive and raise several questions. To further elucidate the host response at brain tissue level, we profiled single-nucleus transcriptomes and performed proteomics from olfactory mucosa, olfactory bulb, medulla oblongata and cerebellum at different timepoints of the disease in individuals who died of COVID-19 and underwent rapid autopsy.

  Study EGAS00001006442

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-010

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Dataset EGAD00001006026

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell renal cell carcinoma -- CA209-025

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Dataset EGAD00001006029

• scRNA-seq of HSPC treated with gemcitabine and carboplatin

  4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. The raw FASTQ-files are available as read 1 and read 2 files from 4 lanes for each sample giving a total of 16 FASTQ-files. The FASTQ-files were also processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression (dge) for each cell of each sample. This has resulted in one dge text file and one dge summary text file per sample. These 8 text-files with dge data are found in the zip-compressed analysis data-file.

  Dataset EGAD00001006080

• Deep amplicon sequencing to infer malignant clonal populations for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  A total of 192 positions per patient were deeply sequenced in each corresponding tumor sample (including 4 experimental controls and SNVs predicted to originate at each node of the sample phylogeny, see Zhang et al. for details). Genomic DNA templates were used as starting material to generate PCR products. PCR was set up using Phusion DNA polymerase according to the manufacturer’s specifications. The standard PCR conditions used were an initial denaturation at 98C for 30 seconds, followed by 35 cycles of 98C for 10 seconds, 60C for 15 seconds and 72C for 8 seconds, and a final extension at 72C for 10 minutes. PCR products were cleaned up using PCRClean DX beads. Amplicons were pooled by template for sequencing sample preparation. Sample preparation involved a second round of amplification using Phusion DNA polymerase with 6 PCR cycles, with primers specified in Zhang et al. DNA quality was assessed using the Caliper LabChip GX HighSensitivity Assay and DNA quantity was measured using a Qubit dsDNA HS assay kit on a Qubit fluorometer. The indexed libraries were pooled together and sequenced on the Illumina NextSeq500 platform with paired-end 150bp reads using v2 chemistry reagents.

  Dataset EGAD00001003986