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

in 40.07 milliseconds.

• 46 patients primary malignant glioma cohort in Chinese population

  We recruited 46 Chinese patients with primary malignant glioma. All the patients were analyzed with whole-exome sequencing (WES) and 27 of them were analyzed with RNA-seq. We compared the molecular features between patients in different WHO grades. We used six-month progression-free survival (PFS6) status to group glioblastoma (GBM) patients to a good and a poor survival compared two groups genomic profiles.

  Study EGAS00001005583

• Epigenetic analyses of methylation and nucleosome occupancy in cell-free DNA (cfNOMe)

  Cell-free DNA (cfDNA) has become essential in cancer diagnostics and prenatal testing. We investigate enzymatic cytosine conversion for epigenetic analyses of cfDNA and find that it reliably measures cytosine methylation and nucleosome occupancy. Whereas previously, separate experiments had to be performed to study either epigenetic marking, this approach delivers reliable results for both, enabling more comprehensive and inexpensive epigenetic profiling of cfDNA.

  Study EGAS00001004370

• Single-cell transcriptome landscape of developing fetal gonads defines somatic cell lineage specification in humans

  We present the comprehensive transcriptional dynamics of cell types populating the male and female developing gonads at a single-cell level. We recovered the gene expression programs of around 128,000 single cells derived from 17 fetal testes and 16 fetal ovaries from 5 to 12 postconceptional weeks. The resulting dataset provides an unprecedented overview of this key period in sex determination and gonadal development.

  Study EGAS00001006568

• 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

• 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

• 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

• 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

• 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

• 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

• ExomeSeq-EGAS00001001306

  Exome Sequencing. 3 μg of genomic DNA from each sample were sheared and used for the construction of a paired-end sequencing library as described in the paired-end sequencing sample preparation protocol provided by Illumina41. Enrichment of exonic sequences was then performed for each library using either the Sure Select Human All Exon 50 Mb or All Exon+UTRs v4 kits following the manufacturer’s instructions (Agilent Technologies). Exon-enriched DNA was pulled down by magnetic beads coated with streptavidin (Invitrogen), followed by washing, elution and 18 additional cycles of amplification of the captured library. Enriched libraries were sequenced (2 × 76 bp) in one lane of an Illumina GAIIx sequencer or in two lanes of a HiSeq2000 when using pools of eight samples.

  Dataset EGAD00001001464

• AML_controls

  Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare hematologic malignancy that is most similar in expression profiles to plasmacytoid dendritic cells. However, patients often exhibit features of AML and can progress to AML. In this project, we will determine the differentially and commonly expressed genes between BPDCN and AML specimens. Available BPDCN and TET2-mutated AML specimens were taken for transcriptome microarray analysis.

  Dataset EGAD00010001726

• A Collaborative Search for New Genes for Non-Syndromic Deafness

  We seek to identify the DNA variants underlying sensorineural hearing loss. We obtain the DNA sequence of affected individuals and their family members. DNA variants are filtered to determine their segregation in affected families.

  Study phs003701

• Metagenomic characterization of tracheal aspirates from non-pulmonary sepsis patients

  Metagenomic characterization of tracheal aspirates from non-pulmonary sepsis patients. This dataset consists of non-human read data from shotgun sequencing in sepsis case samples from lung aspirates. The dataset consist of 32 paired FASTQ files sequenced in paired-read mode 2x150 bp using an Illumina HiSeq 4000 sequencer.

  Dataset EGAD50000000561

• WES of precancerous lesions from 10 lynch patients and 3 sporadics

  Raw sequencing data of WES that were obtained from precancerous samples as adenoma and MMR-deficient crypts and paired healthy tissue from MSI CRC patients of which 10 are diagnosed with lynch syndrome and 3 had sporadic cancer. These data were analyzed in order to evaluate microsatellite instability though tumorigenesis and associated to splicing deregulation in MSI tumors RNA.

  Dataset EGAD50000000644

• A first step towards clinical routine long-read sequencing in Sweden, a national pilot study on chromosomal rearrangements

  PacBio HiFi Revio WGS data from 16 individuals sequenced in the Genomic Medicine Sweden (GMS) Long read project. Each individual was sequenced on one PacBio Revio SMRT cell. The DNA was extracted from blood. The HiFi data was aligned to GRCh38 using minimap2 or the SMRT-link software.

  Dataset EGAD50000000676

• Single-cell RNA-seq of PBMC from 2 patients iGRAN-Low and 2 patients iGRAN-High

  Single-cell RNA-seq of PBMC from 2 patients iGRAN-Low and 2 patients iGRAN-High [Publication title] CXCL8 secreted by immature granulocytes inhibits wildtype hematopoiesis in chronic myelomonocytic leukemia

  Study EGAS50000000556

• Bulk-RNAseq from human nerve fascicles and Schwann cells

  Bulk-RNAsequencing from human nerve fascicles from patients with polyneuropathies, and human Schwann cell cultures isolated from said nerve fascicles, in comparison to control human Schwann cell cultures and a referential fibroblast culture.

  Study EGAS50000000737

• McQuillin_Global_WES_Schizophrenia

  This research project was a collaboration between University College London, UK and the Stanley Center at the Broad Institute. In this project we sequenced and analyzed the whole exomes of 1,623 Schizophrenia, Bipolar and Control samples from collaborators in UK. Genomic DNA from each sample was sequenced to a mean depth of 20x. The exome used Twist capture and samples were sequenced on Illumina HiSeqX machines producing CRAM files.

  Dataset EGAD50000001316

• Targeted sequencing data of cfDNA, archival tissue, and WBC from 226 patients with mUC

  Targeted tissue (n=210), cfDNA (n=402), and WBC (n=245) Illumina sequencing of metastatic urothelial carcinoma patients. All cfDNA is collected in the metastatic setting, while archival tissue is from across the disease course. White blood cell (WBC) samples are used as patient matched germline samples. All files are in paired-end fastq format.

  Dataset EGAD50000001571

• Characterizing Immune Profiles in Extrapulmonary Tuberculosis via RNA Sequencing

  This dataset provides insight into the immune response in extrapulmonary tuberculosis (EPTB), using bulk RNA-seq data to analyze different disease severities. Hierarchical clustering identified three distinct levels of severity, revealing disease progression driven by interferon and IL-1β-mediated signaling. Additionally, the dataset helped develop a diagnostic gene expression signature for both EPTB and pulmonary TB.

  Dataset EGAD50000000943

• Comprehensive analysis of interaction between human gene expression and environmental metagenomes.

  WGS, 10x scRNA, 10X TCR, 10X BCR and CyTOF analyses were performed using blood samples collected from healthy volunteers aged 18 years or older who worked or lived in the Kashiwa-no-ha area.

  Study JGAS000321

• Genomic and transcriptomic analysis on hepatocarcinogenesis after HCV eradication

  Little is known about the genomic and transcriptomic features of hepatocellular carcinoma developing after HCV eradication (SVR-HCC). In this study, we aimed to unveil the genomic and transcriptomic basis of hepatocarcinogenesis after SVR.

  Study JGAS000234

• 419 Japanese healthy control

  Genotypes of 419 Japanese healthy individuals genotyped by using of SNP arrays (Genome-Wide Human SNP Array 6.0 and Axiom Genome-Wide ASI 1 Array). CEL files and CHP files are included in this data set.

  Study JGAS000120

• Targeted sequencing data of cfDNA, archival tissue, and WBC from 208 patients with mUC

  Targeted tissue (n=81), cfDNA (n=319), and WBC (n=208) Illumina sequencing of metastatic urothelial carcinoma patients. All cfDNA is collected in the metastatic setting, while archival tissue is from across the disease course. White blood cell (WBC) samples are used as patient matched germline samples. All files are in paired-end fastq format.

  Dataset EGAD50000002089

• A_study_of_the_molecular_pathogenesis_of_Splenic_Marginal_Zone_and_Diffuse_Large_B_Cell_Lymphoma

  We will perform exome sequencing on selected cases of splenic marginal zone lymphoma (SMZL) and diffuse large B-cell lymphoma (DLBCL) in order to characterise their genetic makeup and identify biomarkers for prognosis and prediction of treatment response.

  Study EGAS00001000335

• Triple_Negative_Breast_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000092

• Transcriptome_Sequencing_of_Cancer_Cell_Lines

  In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Study EGAS00001000261

• Whole-exome analysis of corticotropin-independent Cushing's syndrome

  We performed WES for 8 cases with corticotropin-independent Cushing’s syndrome, in whom paired tumor and normal DNA was obtained from fresh frozen adenomas and either normal adrenal tissues or peripheral blood, respectively.

  Study EGAS00001000661

• RNA seq of MPNST tumour samples

  RNA sequencing of 10 MPNST tumour samples as part of a larger study of MPNST. Article: Lyskjær et al, 2020, J Pathol, "H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours".

  Study EGAS00001004528

• Genomic and Transcriptomic Profile of Paired Primary-Metastasis Colorectal Tumors

  The goal of this study is to identify mechanisms of metastization in a portuguese cohort of colorectal cancer. Namely, we want to identify patterns of genomic and transcriptomic diversification associated with metastasis.

  Study EGAS00001005276

• Tumor HTG EdgeSeq from metastatic castrate resistant prostate cancer

  This dataset contains tumor bulk HTG EdgeSeq from patients with metastatic castrate resistant prostate cancer. RNA libraries were prepared following manufacturer's user guide (HTG Molecular Diagnostics). Each library was sequenced in HTG EdgeSeq system.

  Study EGAS00001004852

• RNA sequencing of high hyperdiploid and ETV6/RUNX1-positive pediatric acute lymphoblastic leukemia

  We performed RNA-sequencing of high hyperdiploid and ETV6/RUNX1-positive ALL cases by using the Human Ribo-Zero rRNA Removal Kit to investigate the gene expression in high hyperdiploid ALL.

  Study EGAS00001003079

• Dedifferentiated_Melanoma_RNAseq

  De- and transdifferentiation of melanoma is a rare histopathological phenomenon that has not be characterised genetically. In this project we plan to sequence the genomes of de and transdifferentiated cases so as to define their genetic make-up.

  Study EGAS00001003601

• Targeted DNA sequencing on 37 Merkel Cell Carcinomas from New Zealand with known Merkel cell polyomavirus status

  To determine the genomic landscape of NZ virus-negative MCCs (VN-MCC), assess genomic evolution in metastases, and catalogue the distribution of TP53 and RB1 variants from international studies.

  Study EGAS00001006873

• RNA-Seq data from 34 CAF-S3 subset in human breast and ovarian cancers

  This dataset is related to publications Costa et al. Cancer Cell 2018 and Givel et al. Nat. Commun. 2018 which describe the identification of 4 Cancer Associated Fibroblasts (CAF) in breast and ovarian cancer. This dataset contains transcriptomic profiles obtained by RNA-Seq of 34 CAF-S3 samples from breast and ovarian Tumors.

  Dataset EGAD00001004810

• Pre-post neoadjuvant chemotherapy breast cancer dataset- RNAseq data

  This dataset contains RNAseq data of 20 paired pre-post neoadjuvant chemotherapy breast cancer samples. In total the set contains n=20 biopsies, n=20 surgery specimens. Each sample has 2 fastq files, so n=80 fastq files are uploaded in total.

  Dataset EGAD00001008421

• Whole-transcriptome characterization of cell-free RNA (cfRNA) in cancer and non-cancer patients

  Whole-transcriptome characterization of cfRNA in cancer (stage III breast [n=46], lung [n=30]) and non-cancer (n=89) participants from the Circulating Cell-free Genome Atlas (NCT02889978). Dataset includes collapsed BAM files for plasma cfRNA from each patient, as well as collapsed BAM files for RNA from matched tumor tissue (when available).

  Dataset EGAD00001006484

• Single cell transcriptomics of adult human adrenal gland

  Single cell transcriptomics (10x 3') of human adrenal gland. The adrenal gland of this particular individual is characterized by the presence of mutant clone characterized by aneuploidy in chromosomes 8, 9, 13 and 22, occupying the zona glomerulosa and zona fasciculata. This dataset contains the primary sequencing data generated from the 10x genomics 3' library in fastq format.

  Dataset EGAD00001011288

• High-coverage whole genome sequencing of human populations from the Pacific

  This dataset includes high-coverage genomes (~36x) of 317 individuals from 20 populations of the Pacific (Taiwan, Philippines, Solomon Islands, Vanuatu archipelago), described in “Genomic insights into population history and biological adaptation in Oceania”, by Choin, Mendoza-Revilla, Arauna, and colleagues (Nature 2021). The data is made of 331 fastq files.

  Dataset EGAD00001006880

• CGH Array

  DNA samples were extracted from peripheral blood lymphocytes using commercially available kit (Puregene Core Kit A, Qiagen) according to manufacturer's protocol. Agilent SurePrint G3 Human CGH Microarray 180K platform was used for screening of copy number aberrations (CNAs) using array-CGH protocol recommended by manufacturer (Agilent Technologies), data mining and interpretation of array-CGH results was performed in same manner as in our previously published results.

  Dataset EGAD00001007743

• Stitched BAM files for manuscript titled Discrepancies in Tumour Mutation Burden (TMB) reporting from sequential Endobronchial ultrasound trans bronchial needle aspiration (EBUS TBNA) samples within single lymph node stations for SNP and INDEL Variant Calling.

  Stitched BAM files for manuscript titled Discrepancies in Tumour Mutation Burden (TMB) reporting from sequential Endobronchial ultrasound trans bronchial needle aspiration (EBUS TBNA) samples within single lymph node stations for SNP and INDEL Variant Calling.

  Dataset EGAD00001012639

• 10x genomics RNAseq of an isogenic human iPSC model of SMA

  10x genomics single-cell RNAseq of an isogenic human iPSC model for SMA and control. The transcriptomic analysis was performed at 3 timepoints, day 4, day 20 and day 40. The analysis of this dataset was reported in the manuscript "An isogenic human iPSC model unravels neurodevelopmental abnormalities in SMA" from Grass et al.:

  Dataset EGAD00001011259

• Whole genome sequencing of adult glioblastoma nuclei

  Three primary adult glioblastoma specimens were dissociated and nuclei were extracted. A portion of the nuclei was used for single-cell ATAC seq and the remainder were submitted for whole genome sequencing, to provide orthogonal validation of copy number variations in the samples compared to single-cell ATAC seq. Samples were sequenced on the Illumina NovaSeq 6000 in paired-end mode.

  Dataset EGAD00001007651

• Glioblastoma CRISPR Screen (2016-06-02)

  This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs. This dataset contains all the data available for this study on 2016-06-02.

  Dataset EGAD00001002158

• CNV detection in targeted NGS panel data

  We present targeted NGS panel data from 170 samples that were processed using the TruSightTM Cancer (TSC) panel (Illumina, San Diego, CA, USA), which targets 94 genes and 284 SNPs associated with a predisposition towards cancer. The samples are enriched for CNVs in the genes of interest. All CNVs have previously been assessed with MLPA and can therefore be considered as confirmed.

  Dataset EGAD00001003400

• Epigenetic profiling of colorectal cancer initiating cells (CC-ICs) and investigation of changes in transcriptome following EZH2 inhibition using RNA-seq.

  Epigenetic profiling of colorectal cancer initiating cells (CC-ICs) to identify bivalently marked genes (H3K4me3 and H3K27me3 ChIP-seq), and investigation of changes in transcriptome following EZH2 inhibition using RNA-seq.

  Dataset EGAD00001004133

• Thirty cutaneous SCC WES tumour samples with matched normal

  Thirty cutaneous SCC WES tumour samples with matched normal include 20 samples from South et al. JID and 10 new samples. These 30 samples has been used to support the findings in the TGFb Nature Communications paper (DOI: 10.1038/ncomms12493). They are also a part of the ongoing study of cSCC genomic landscape of 40 cSCC samples in total.

  Dataset EGAD00001002253

• Glioblastoma CRISPR Screen (2017-04-27)

  This is an in vitro genome-wide CRISPR/cas9 screen in human glioblastoma stem cells, screening for genes essential for survival of these cells. These cells express cas9 and have been transfected with a guide RNA library causing gene knockouts. We will analyse the sequencing data for depletion of guide RNAs. This dataset contains all the data available for this study on 2017-04-27.

  Dataset EGAD00001003308

• Somatic mutations in 106 small intestine adenocarcinoma

  106 FFPE tumor samples from small bowel were sequenced with Illumina HiSeq 4000. Exome capture was performed with NimbleGen SeqCap EZ Exome Library v3 Kit. Reads were aligned with BWA–MEM v.0.7.12 to GRCh37 reference genome. Variant calls were produced with GATK HaplotypeCaller. Variant calls were filtered against all data from gnomAD database using allele frequency threshold 0.0001 in order to remove germline variation.

  Dataset EGAD00001003802

• Targeted Pulldown Validation of mutations found in whole genome sequencing

  This experiment is to inform us of the validity of using pre-made library material to perform a bespoke pulldown experiment to validate the mutations found between the whole genome sequencing of the DNA from the same individuals cancer and normal material. This is to identify the valid and informative mutations in cancer genomes.

  Dataset EGAD00001001061

• GILD-ExomeSeq-PTNHL

  This study is meant to gain further knowledge in haematological cancers. Patients samples (mainly DNAs or PCR products) from haematolocical cancer patients will be sequenced, and the outputs will be correlated to their diagnosis and/or prognosis; the findings may also add more insight into the understanding of biology in this type of tumour. We will be sequencing Primary Testicular Lymphomas (PTL) to identify genetic drivers of this rare cancer

  Dataset EGAD00001001986

• Colorectal cancer WES/WGS analysis in Dr. Liu’s group in Sun Yat-sen University Cancer Center

  The samples include paired tumor and normal tissues from 205 patients (201 for normal and primary tumor tissues; 4 for normal, primary tumor and liver metastatic tissues). High-coverage WES sequencing or whole genome sequencing of DNA samples were performed on the Illumina HiSeq 2000 system

  Dataset EGAD00001003452

• Rare germline variants of acute myeloid leukemia patients

  The dataset (vcf files) consists of rare germline variants of 68 Finnish acute myeloid leukemia patients. We performed exome sequencing and filtered the germline variants against ExAC total MAF<0.01 in two gene panels. The 35 genes in the panels studied here have previously been associated with hematological malignancies and/or solid tumors. The dataset contains only variants of the two gene panels.

  Dataset EGAD00001003894

• Dataset for the study - Detection of cell-free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients

  FASTQ files from sequencing to < 0.4x depth of coverage of thirteen glioma patients. Indexed sequencing libraries were prepared using a commercially available kit (ThruPLEX-Plasma Seq, Rubicon Genomics). Libraries were pooled in equimolar amounts and sequenced on a HiSeq 4000 (Illumina) generating 150-bp paired-end reads.

  Dataset EGAD00001004425

• Whole-genome sequencing of paired tumor and blood samples from 65 bladder cancer patients

  65 paired tumor and normal whole-genome sequencing samples from urothelial bladder carcinomas (UBC, the most common type of bladder cancer) are used to uncover the whole-genome mutational landscape of UBC. Recurrent mutations in noncoding regions affecting gene regulatory elements and structural variations leading to gene disruptions are prevalent in this type of cancer.

  Dataset EGAD00001004545

• Dataset Gene-Breakpoint Panel

  In this study we analysed patients with metastatic prostate cancer to scan their tumor genomes noninvasively in plasma DNA. We enriched 1.3 Mbp of seven plasma DNAs (4 CRPC cases: CRPC1-3 and CRPC5; 3 CSPC cases: CSPC1-2 and CSPC4) including exonic sequences of 55 cancer genes and 38 introns of 18 genes, where fusion breakpoints have been described using Sure Select Custom DNA Kit.

  Dataset EGAD00001000365

• RNAseq of ribosomal footprints

  Cancer genes can affect ribosomal RNA processing and this can underlie their essentiality to cells, making them cell-essential in the same way as ribosomal genes themselves. We want to confirm this, in order to understand the results of our CRISPR drop-out screens.NOTE FROM BESPOKE TEAM: Run a single read 1 (forward read) of 30 bases, then an index 1 read as normal. This would fit a 50cycle kit

  Dataset EGAD00001001930

• TTV018 RORC IBD-associated genotype effects on RORgT expression and function in ex vivo T cells

  RNA sequencing of peripheral immune cells from patients +/- an IBD risk variant. Peripheral immune cells +/- in vitro test compound treatment. 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 EGAD00001002233

• Re-aligned BAM files for manuscript titled Discrepancies in Tumour Mutation Burden (TMB) reporting from sequential Endobronchial ultrasound trans bronchial needle aspiration (EBUS TBNA) samples within single lymph node stations for Copy Number Variant Calling.

  Re-aligned BAM files for manuscript titled Discrepancies in Tumour Mutation Burden (TMB) reporting from sequential Endobronchial ultrasound trans bronchial needle aspiration (EBUS TBNA) samples within single lymph node stations for Copy Number Variant Calling.

  Dataset EGAD00001012638

• Exome Atlas in HCC tumors

  The atlas provides a comprehensive exploration of genetic and transcriptomic landscapes within HCC, offering insights into key genomic alterations and gene expression patterns. The integration of exome sequencing and RNAseq data enhances our understanding of the molecular complexity underlying HCC, potentially paving the way for targeted therapeutic strategies and biomarker discovery in the context of hepatocellular carcinoma.

  Dataset EGAD00001015342

• Transcriptomic Data for Manuscript with title: Comprehensive genomic profiling in esophageal adenocarcinoma unmasks potential precision therapies

  Transcriptomic Data for Manuscript with title: Comprehensive genomic profiling in esophageal adenocarcinoma unmasks potential precision therapies

  Dataset EGAD00001015476

• MGRB dataset. Samples that were not included in the paper.

  This dataset comprises 1440 whole genome sequenced samples from the Medical Genome Reference Bank. https://sgc.garvan.org.au/initiatives/mgrb The files are provided in cram format, aligned to hs37d5 with decoys, with no further processing applied. The dataset also contains phenotype information for each sample.

  Dataset EGAD00001005095

• RRBS DNA methylation analysis of in vitro differentiation from induced pluripotent stem cells to hepatocyte-like cells

  Fastq files of Reduced Representation Bisulfite Sequencing data (HaeIII, covering about 7 million CpGs per sample) of induced pluripotent stem cells (iPSC), definitive endoderm (DE) and hepatocyte-like cells (HLC). The dataset comprises data generated by the in vitro differentiation protocol Cellartis (Takara Bio, "CEL", n = 4).

  Dataset EGAD00001005933

• Bulk RNA sequencing data in "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2"

  This dataset includes 14 bulk RNA sequencing data (28 fastq files) in the study entitled "Three-dimensional human alveolar stem cell culture models reveal infection response to SARS-CoV-2". RNA sequencing library was generated with Truseq stranded total RNA Gold kit.

  Dataset EGAD00001006241

• Effect of ETS2 modulation on chromatin accessibility and enhancer activity in inflammatory (TPP) macrophages

  This dataset consists of H3K27ac ChIP-seq and ATAC-seq in primary human macrophages following modulation of ETS2 expression. There are three datasets: H3K27ac ChIP-seq in ETS2-edited and unedited inflammatory (TPP) macrophages, H3K27ac ChIP-seq in ETS2-overexpressing and control M0 macrophages, and ATAC-seq in ETS2-edited and unedited inflammatory macrophages. For editing experiments, monocytes were transfected with CRISPR-Cas9 ribonucleoproteins containing a gRNA that was validated to edit ETS2, or a non-targeting control gRNA. Inflammatory macrophage differentiation was performed using conditions that model chronic inflammation (TPP): 3 days GM-CSF (50ng/mL) followed by 3 days GM-CSF, TNFa (50ng/mL), PGE2 (1mg/mL), and Pam3CSK4 (1mg/mL). For overexpression experiments, controlled overexpression of ETS2 mRNA or control mRNA (an equivalent amount of mRNA encoding the reverse complement of ETS2 – thereby controlling for the quantity, length and purine/pyrimidine composition of the transfected RNA but with a transcript that would not be translated) was induced in resting, non-activated (M0) macrophages by transfecting 500ng mRNA. To minimise non-specific activation due to the transfected RNA, in vitro transcription was performed using co-transcriptional capping (to minimise uncapped products), and incorporating modified, minimally immunogenic nucleotides (replacing uridine with N1-methyl-pseudouridine and cytidine with methylcytidine). After 18 hours, transfected cells were were activated with low dose LPS and harvested 6 hours later. For H3K27ac ChIP-seq, cells were harvested, cross-linked, quenched, lysed, and sheared. Immunoprecipitation of histone-DNA complexes was performed overnight at 4C with rotation using an anti-H3K27ac antibody and the SimpleChIP Plus Sonication ChIP kit (Cell Signaling Technology). Following reverse cross-linking, 50ng of immunoprecipitated DNA or input DNA were used to prepare sequencing libraries using the iDeal Library Preparation kit (Diagenode), according to manufacturer instructions. 10 PCR cycles were used for the amplification step and size selection was not performed. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 (Agilent) and the libraries were sequenced on an Illumina NovaSeq 6000. Raw data are provided as raw and aligned sequencing reads from H3K27ac-bound DNA and the input chromatin. ATAC-seq in TPP macrophages was performed using the Omni-ATAC protocol (Corces et al 2017) with the following modifications: cell number was increased to 75,000 cells, cell lysis time was increased to 5 minutes; volume of Tn5 transposase in the transposition mixture was doubled; duration of the transposition step was extended to 40 minutes. Sequencing libraries were prepared by PCR with the NEBNext Ultra II Q5Master Mix (NEB) as described previously (Corces et al 2017). Amplified libraries were cleaned using AMPure XP beads (Beckman Coulter). Sequencing reads were trimmed using TrimGalore! (Phred score 24), filtered to remove reads < 20 bp and aligned to the human genome (hg19) using Burrows-Wheeler Aligner (BWA). Aligned reads were converted to BAM files, sorted and indexed using SAMtools (Li et al, 2009). PCR duplicates and unmapped reads were removed, and the resulting BAM files were re-sorted and indexed. Raw data are provided as 100 bp paired-end Illumina reads from n = 3 donors for each experiment. BAM files are also provided.

  Study EGAS50000000109

• NHLBI TOPMed: My Life Our Future (MLOF) Research Repository of Patients with Hemophilia A (Factor VIII Deficiency) or Hemophilia B (Factor IX Deficiency)

  Hemophilia A and B are X-linked bleeding disorders resulting from a deficiency in coagulation factor VIII (FVIII) or factor IX (FIX), respectively. Hemophilia affects approximately 1/5000 male births worldwide, and results in premature death and disability due to bleeding if coagulation factor replacement therapy is not used effectively. Hemophilia is clinically categorized by coagulation factor activity levels and ranges in severity from mild (6% to 30%) to moderate (1-5%) to severe (&lt;1%). Many female "carriers" of hemophilia also have decreased factor activity and morbidity from bleeding. Hemophilia A and B are almost always caused by identifiable mutations in the F8 and F9 genes, respectively, and these mutations are found throughout the structural genes. Although the hemophilias are monogenic disorders, there are wide variations in disease severity and therapeutic outcomes which are not readily explained by the disease causing mutations alone. The My Life Our Future (MLOF) project (www.mylifeourfuture.org) is a national resource developed by a partnership of BloodworksNW (BWNW, formerly the Puget Sound Blood Center), the American Thrombosis and Hemostasis Network (ATHN), the National Hemophilia Foundation (NHF) and Bioverativ, to provide free F8 and F9 gene variant analysis to patients with hemophilia A or B, and to establish a research repository of DNA sequence, DNA, RNA, buffy coat, serum and plasma. The sequence analysis and serum samples are linked to a phenotypic database hosted by ATHN, with samples submitted and clinical data entered at ~100 hemophilia treatment centers (HTCs) nationwide. (See ATHN Research Report Brief in the resource center at www.athn.org). MLOF has become the largest hemophilia genetic project worldwide. The roles of the MLOF partners are: BWNW, to serve as the central laboratory for the project and house the research repository; ATHN, to support and provide the administrative link with HTCs, to facilitate the collection of accurate phenotypic data, to conduct research review and approval for use of the repository and with BWNW to provide samples and data for research projects; NHF, to provide consumer education and facilitate consumer input into the project; and Bioverativ, to provide financial support and scientific input. The project is governed by a Steering Committee consisting of one representative from each organization. Subject samples chosen from the MLOF parent study for TOPMed and WGS were drawn from those who gave (or parents gave) informed consent for the Research Repository and included patients of all severities and type, but with an emphasis on those with severe hemophilia and others at increased risk of neutralizing antibody (inhibitor) formation and who had samples in the Research Repository (plasma, serum, RNA) for potential additional -omic studies. Also included were samples from subjects where a likely causative variant for hemophilia was not found in the F8 or F9 coding region, intron-exon boundaries or immediate upstream and downstream regions. Since hemophilia is an X-linked disorder, the majority of subjects are male. Racial distribution is similar to the overall population distribution.

  Study phs001515

• Submitter Portal API

  Submitter Portal API The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. For those that want a more flexible and automated approach, we also provide a programmatic approach using the Submitter Portal AP in addition to the user interface of the Submitter Portal. With the help of our API, you can quickly include the submission of metadata into your own workflow for a more effective and individualised experience. Previous steps Create your EGA account To submit data you first need to create your EGA user. Then, once your account has been verified, you will have to request a submitter role and sign the EGA Data Processing Agreement (DPA). When the DPA is signed, you must send it to EGA Helpdesk for further validation. Please, note that if you already have an EGA account, or you have an ega-box (submission account), you can skip this step.  Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find the relevant information in the DAC Portal Guide. Programmatic submission All the calls to the API need to be Authenticated. We use the OpenID Connect protocol. API Usage Flow: Click here to check the API usage flow schema Obtain Access and Refresh Token: The first step to using the API is to obtain an access and refresh token. These tokens are required for authentication and authorisation of API requests. To obtain these tokens, you need to log in using your EGA credentials. Example: curl "https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token" \ -d "grant_type=password" \ -d "client_id=sp-api" \ -d "username=your-username" \ --data-urlencode "password=your-password" Use Access Token in API Calls: Once you have obtained the access token, you must use it in all the calls to the API. The access token is valid for a limited time period. When it expires, you will need to use the refresh token to obtain a new access token. Create Submission Object: After authentication, you can start creating a submission object. This object will be used to store all the metadata objects and files related to the submission. Example: curl "https://submission.ega-archive.org/api/submissions" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" \ -d "{ \"title\":\"My submission title\", \"description\":\"My submission description\" }" Create EGA Metadata Objects: Within the submission object, you can create other metadata objects required for the submission. These objects may include information about the submitter, study, sample, experiment, and run. Example of study creation: curl "https://submission.ega-archive.org/api/submissions/{submisison-id}/studies" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" \ -d "{ \"title\":\"My study title\", \"description\":\"My study description\", \"study_type\":\"Metagenomics\" }" If you would like to reuse already registered objects in new submissions, bear in mind that they must have an accession which you must use to reference them. You cannot reuse objects that have not been finalised and accepted yet.For example, when creating a new run which is reusing a previously submitted experiment, instead of using experiment_provisional_id, you must use experiment_accession_id. Enums There are some fields that only accept specific values, i.e. study_type. The API provides several enumerations to list these values. You can list all the enumerations, or a specific one, for example, study_types. Obtain IDs of files You can list the files available in your inbox and filter by a prefix by adding the prefix param, i.e. &prefix=/my_folder/abc Example: curl "https://submission.ega-archive.org/api/files?status=inbox&prefix=/my_folder/abc" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" To improve performance and manageability, we have limited the number of files that the Submitter Portal API can return in a response. If a given call exceeds this limit, user will be asked to narrow down the search by using the query parameters already available in this endpoint. Finalise Submission: Once all the metadata objects are created and linked to the submission, you can finalise the submission. Finalising the submission sends it to the Helpdesk team for review. Please, note that all files linked to the submission must be ingested, and all objects created in a submission must be linked before you can finalise the submission. API Reference: For a full API reference, please check our specification documentation.

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal-api

• Determination of Cross-Reactive Immunological Material (CRIM) status and longitudinal follow-up of individuals with Pompe disease

  Infantile-onset Pompe disease is an inherited disorder that is normally diagnosed within the first months of life. It is caused by lack of or defect in an enzyme (a special protein that carries out normal chemical reactions within the body) called acid alpha-glucosidase (GAA). GAA normally breaks down glycogen (stored sugar) in lysosomes (the part of the cell that digests food and other chemicals). Pompe disease is one of many lysosomal storage diseases (LSDs). LSDs are diseases caused by the malfunction of the lysosome or one of their digestive enzymes. Patients with Pompe disease cannot break down lysosomal glycogen. This causes glycogen to build up and damage cells throughout the body, especially in the heart and muscles. Current treatment for Pompe disease involves enzyme replacement therapy (ERT). In this treatment, the drug alglucosidase alfa (Myozyme) is put into your blood. The drug provides a form of the GAA enzyme to replace the enzyme that is missing or not working properly in the patient&#39;s blood. This treatment has allowed babies to live longer and achieve developmental milestones. In this study, researchers will learn about the patient&#39;s ability to tolerate ERT. Cross-Reactive Immunological Material (CRIM) is a measurement of natural GAA production. A patient&#39;s CRIM status (either positive or negative) is an important factor that affects how he or she responds to ERT with Myozyme. Children who produce some natural GAA are classified as CRIM+, while children who do not produce any natural GAA are classified as CRIM-. Children who are CRIM+ generally tolerate ERT well. But, children who are CRIM-, and some children classified as CRIM+, have a poor response to ERT. Patients who have a poor response to ERT have complications because their body sees Myozyme as "foreign" and triggers an immune response to try to remove it from the body. Treatments are currently being developed to stop this immune response and prevent complications from ERT. We will enroll patients with Infantile Pompe disease in this longitudinal natural history (observational) study. The specific aims of this study are: To determine and correlate Cross-Reactive Immunological Material (CRIM) status with the GAA gene mutations found on these patients To validate an approach for determining CRIM status from whole blood sample, with the gold standard determination of CRIM status by skin fibroblasts and mutation analysis To explore the clinical treatment response and natural history of CRIM-positive and CRIM-negative Pompe disease patients with and without immune modulation To investigate the role of immune response to treatment

  Study phs001555

• Prader-Willi Syndrome and Early-onset Morbid Obesity Natural History Protocol

  This observational study will involve the comprehensive assessment of the medical, behavioral and nutritional history and the clinical features of individuals with Prader-Willi syndrome and individuals with features of PWS-like/EMO. A blood sample will be obtained from the participants in order to create a DNA and RNA repository. In those PWS participants with a known deletion a blood sample will be collected for DNA in order to perform array comparative genome hybridization (aCGH) microarray or Methylation-Specific Multiplex Ligation-dependent Probe Amplification (MS-MLPA) studies to characterize the extent of the deletion. DNA samples will be sent to the Consortium Center at Baylor College of Medicine for the performance of the aCGH studies and to either Dr. Driscoll or Dr. Butler lab for MS-MLPA analysis. No drugs or treatments will be administered through this protocol. Our goal is to enroll as many participants as possible over a 8 year period. Currently we have enrolled 297 total subjects of which 265 have PWS and 32 EMO. Our original goal was to have enrolled over the first 5 years a clinical database of 200 individuals with PWS and 100 with EMO. We have exceeded expectations in PWS enrollment, but have fallen short in the enrollment of individuals with EMO. Therefore, we would like to reset our goals. We now propose to have an enrollment goal of 400 total subjects of which 350 will have PWS and 50 will have EMO. Eligible participants will be initially enrolled in the natural history study from the 4 clinic sites currently involved with PWS (University of Florida, Kansas University Medical Center, Vanderbilt University and University of California at Irvine). Participants assessed will serve to provide a background of information and a willing cohort for future interventional studies. All participants will have had standard genetic testing at a commercial laboratory prior to entry into the study. The PWS participants will be classified into one of the 3 main molecular classes (deletion, UPD and ID). The EMO participants will have had laboratory testing ruling out PWS and chromosomal aneuploidy (e.g., trisomy 21, Klinefelter syndrome, etc.). Going forward we feel it is important that all newly recruited EMO subjects have an aCGH as part of their evaluation so we can identify those with discrete deletions, duplications or copy number variants (CNV) and compare them to those without aCGH abnormalities. The participants will be assessed annually (0-3 years of age) or biennially (&#62; 3 years) in the Clinical Research Center (or equivalent facility) using standardized protocol including photographs for documentation purposes to compare the evolution of the clinical phenotype.

  Study phs000575

• National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III)

  The National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) is a nationally representative cross-sectional survey of the U.S. general population, which was sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and conducted in 2012-2013. The NESARC-III's target population was the U.S. noninstitutionalized civilian population, 18 years and older, including residents of selected group quarters (e.g., group homes, workers' dormitories). Multistage probability sampling was used to randomly select respondents. Primary sampling units (PSUs) were individual counties or groups of contiguous counties, secondary sampling units (SSU) comprised groups of Census-defined blocks, and tertiary sampling units were households within SSUs. Finally, eligible adults within sampled households were randomly selected. Hispanics, Blacks, and Asians were oversampled and resulted in a total of 36,309 respondents. All respondents provided informed consent for survey participation. Data were adjusted for oversampling and screener - and person-level nonresponse, then weighted through post-stratification to represent the US civilian population based on the 2012 American Community Survey. These weighting adjustments were found to compensate adequately for nonresponse. Interviewer field methods involved initial structured home study, in-person training, ongoing supervision, and random respondent callbacks to verify data. The NESARC-III collected information on alcohol and drug consumption, alcohol use disorder, other substance use disorders (e.g., nicotine, cannabis and opioid), and associated physical and psychiatric adverse consequences. In addition to a full array of sociodemographic characteristics such as race/ethnicity, gender, age, risk and environmental factors including adverse childhood experiences (e.g., sexual, physical abuse and neglect) and family history for alcohol, drug use disorders and other psychiatric disorders (e.g., mood, anxiety, personality disorders and PTSD) were included (phenotypic variables=4,320). As part of the NESARC-III, 22,848 informative samples were genotyped on Affymetrix Axiom Exome Array consisting of 319,283 SNPs and 103,404 custom-selected SNPs Array (refer to the SNP annotation file). The latter array was selected based on the addiction associated genes, the results of 5 GWAS of alcohol and other psychiatric disorders, and animal models with addiction phenotypes. After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data. The 22,848 subjects in this study were all deeply and consistently phenotyped via structured diagnostic interview. Controls group can be selected for specific disorders from a pool of all samples. Here are numbers of cases for major DSM-5 mental disorders in NESARC-III genetic data: Alcohol use disorder (7,075); Nicotine use disorder (6,641); Drug use disorder (2,570); Major depressive disorder (5,214); Persistent depression(1,429); Bipolar I (543); Anxiety disorders (4,226); PTSD (1,674); Personality disorders (4,014); Eating Disorders (457).

  Study phs001590

• How to request data

  Request Data Access If you're looking to access data from the EGA for your research, you are in the right documentation page! In this page you will find a step by step guide on how to request data archived at the EGA, as well as some frequently asked questions you might find useful. When requesting data, you'll need to provide information about your research project and intended use of the data. Keep in mind that your data access request may require additional approvals or agreements depending on the datasets and data providers involved. Step by step guide Register yourself as an EGA user. Validate your account. A validation link will be sent to your email to activate your EGA user account. Log into the EGA page. Search the dataset of interest from the dataset catalogue or search bar. Click on “Request access” Add a comment requesting these files and send your request Your request is successfully registered, and the DAC will receive a notification about your request In addition to submitting your request, you should also contact the DAC directly via e-mail. You can access the DAC's contact information from the relevant dataset page. Frequently Asked Questions (FAQ) Which is the role of the EGA in the data access process? The European Genome-phenome Archive (EGA) facilitates the secure distribution under controlled access of personally identifiable genetic and phenotypic data. Data Access Committee (DAC) is a body of one or more individuals who are responsible for data release to external requestors, based on participant consent and/or National Research Ethics terms. How do I request access to multiple datasets? To request access for multiple datasets managed by the same Data Access Committee (DAC), please start by visiting the DAC catalogue to locate the DAC of your choice. Once you've found the relevant DAC, proceed to its dedicated page where you'll find a "Request access" button. After logging in to the EGA website, you'll be presented with a comprehensive list of datasets under the chosen DAC. Select the datasets you're interested in, and then compose a message indicating your access request. Click the "Send" button to submit your request, which will include the chosen datasets. Please be sure to review the data usage policies for the requested datasets, as policies can vary among datasets managed by the same DAC. I am a co-applicant. Will I be given a joint access account? Each applicant needs to create an EGA account themselves, with unique login details. User log-in details are for individual use only and should never be shared, under any circumstances. EGA services are only provided to EGA account holders. Therefore, the co-applicant will send a formal request to the DAC. What happens if a co-applicant leaves or a new member needs to be added to an existing DAC application? The appropriate Data Access Committee (DAC) should be contacted and informed about the required changes so that the application can be updated. I have changed my place of work since my EGA account was created. Can I still have access to data? You must contact the relevant Data Access Committee (DAC). The DAC did not reply to my data access request. How should I proceed? There is no estimated time for DAC response. Please allow up to four weeks for a response. In the meantime, please send them a weekly reminder of the status of your request by emailing them directly.If the DAC becomes unresponsive, meaning that they fail to communicate with a requestor within the specified time frame, please contact the EGA Helpdesk team. I have an account with the EGA and would like access to further datasets. How should I proceed? You need to reapply to the relevant Data Access Committee (DAC). Once the DAC has approved your application your account will be updated and an email will be sent to notify you of a change made to your account. How do I download files of the datasets I have been granted access to? The preferred method for data download and decryption is the EGA Secure Download Client. Please carefully review the provided documentation. How do I download metadata? Metadata is retrieved from the EGA webpage; you will not need to use any download client. Be informed that you will only be able to download metadata of your approved datasets. For such download, you should first log in the EGA webpage with your credentials. Then browse the metadata's dataset you have gained access and you will find a metadata download button. You may also want to have a look our metadata schema. I have forgotten or misplaced my user account password; how do I get a new one? Click on “Log in”, located in the top right corner of the EGA homepage. Then click “Forgot password”, type in your registered institutional email address, and instructions for resetting your password will be sent to you. Please check both regular and junk/spam folders. I was sent a link to set a password for my download account, but it seems like the link has expired. What should I do? The procedure is the same as the one for a forgotten password, explained in the previous question.

  Documentation access/request-data/how-to-request-data

• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI&#39;s Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON&#39;s overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

  Study phs001265

• Assessing Neural Mechanisms of Injury in Inborn Errors of Urea Metabolism Using Structural MRI, Functional MRI, and Magnetic Resonance Spectroscopy

  Urea cycle disorders represent a group of rare inborn errors of metabolism that lead to accumulation of ammonia, a toxic product of protein metabolism. Individuals with urea cycle disorders cannot metabolize the ammonia that accumulates due to enzyme deficiency. The symptoms of these disorders may present at birth, childhood or adulthood (milder deficiencies). There are currently eight enzyme deficiencies that constitute the range of inborn errors of ureagenesis. This project will focus on the most common enzyme disorder of the urea cycle, ornithine transcarbamylase deficiency, inherited as an X-linked trait. This project will study cognitive and motor dysfunction in patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non -invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies will range from ages 18-60 years and will be compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

  Study phs001108

• San Francisco Bay Area Latina Breast Cancer Study

  The genome-wide association study (GWAS) includes participants enrolled into two different studies. The first study, the San Francisco Bay Area Cancer Study (SFBCS) is a population-based case-control study of breast cancer conducted in the San Francisco Bay Area and included women ages 35-79 years from three racial/ethnic groups: Non-Hispanic whites, African Americans, and Hispanics/Latinas. For the GWAS, only Hispanic/Latina women were included. Women diagnosed with invasive breast cancer between 1995 and 2002 were identified through the Greater Bay Area Cancer Registry. Controls were identified by random digit dialing and were frequency-matched to cases by age in 5 year increments and by race/ethnicity. Hispanic/Latina ethnicity was assessed by self-report. 175 Hispanic/Latina cases and 307 Hispanic/Latina controls from the SFBCS had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission. The second study is the Northern California site of the Breast Cancer Family Registry (NC-BCFR). This population-based family study recruited breast cancer cases ages 18-64 years diagnosed from 1995-2009 that were identified through the Greater Bay Area Cancer Registry. Cases included all women at increased genetic susceptibility for breast cancer who met one or more of the following criteria: (a) being diagnosed with breast cancer at age &#60;35 years; b) having a personal history of ovarian cancer or childhood cancer; (c) being diagnosed with two different breast cancers (bilateral breast cancers), with the first one diagnosed at age &#60;50 years; and d) having one or more first-degree relatives with breast cancer, ovarian cancer or childhood cancer. Cases not meeting these criteria were randomly sampled and racial/ethnic minorities were oversampled. Controls were recruited by random digit dialing and were matched by 5-year age increments and by race/ethnicity. For the current GWAS only Latina/Hispanic cases and controls were included. Latina/Hispanic ethnicity was assessed by self-report. 631 Hispanic/Latina cases and 61 Hispanic/Latina controls from the NC-BCFR had given adequate consent and provided biospecimens that were used in the GWAS to be included in this data submission.

  Study phs000912

• National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study, the Framingham Heart Study, the Jackson Heart Study, and the Multi-Ethnic Study of Atherosclerosis. Together, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African-American, Caucasian, Asian, and Hispanic ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000398 contains the Atherosclerosis Risk in Communities (ARIC) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP.

  Study phs000398

• Center for Common Disease Genomics [CCDG] - Cardiovascular: Genetic and Phenotypic Determinants of Blood Pressure and Other Cardiovascular Risk Factors

  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 &gt;20,000 individuals with AF and &gt;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: ccdg.rutgers.edu The GAPP study is an ongoing national population-based prospective cohort study conducted in the Principality of Liechtenstein. Between 2010 and 2014, all inhabitants of Liechtenstein aged 25-41 years old were asked to participate in the study, and 2170 could be enrolled. The aim of the study is to identify the determinants of blood pressure and other cardiovascular risk factors and their progression over time. A large number of baseline characteristics and health information as well as several blood, urinary and genetic markers were collected. The samples were sent to The Broad Institute of MIT and Harvard to generate genetic data using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array); all samples serving as controls.

  Study phs002236

• NHLBI GO-ESP Family Studies: Idiopathic Bronchiectasis of unknown etiology that is not related to cystic fibrosis or classic primary ciliary dyskinesia or immune deficiency or any other known causes

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The major goal of this project is to apply next generation resequencing technology to identify disease-causing variants that cause bronchiectasis of unknown etiology (e.g. non cystic fibrosis (CF), classic primary ciliary dyskinesia (PCD), immune deficiency, or any other known cause of bronchiectasis), i.e., "idiopathic bronchiectasis." As part of our ongoing efforts to define the genetic cause of rare lung diseases, we have also studied families in whom diagnosis of PCD or other known etiologies could not be confirmed. We have systematically collected and stored the DNA and phenotypic data on each of the families in our cohort. The phenotypic data includes age, gender, ethnicity information, clinical data pertaining to the airways disease, including neonatal respiratory distress, otitis media, sinusitis and bronchiectasis, ciliary ultrastructure analysis, and microbial colonization (status of nontuberculosis mycobacterium). During the course of our study, we have acquired 98 unrelated patients in whom bronchiectasis seemed to be of unknown causes. We will be using 11 unrelated patients, 5 unrelated affected sib-pairs, and 3 affected sibs from a family from this cohort, based on 1) development of bronchiectasis in the absence of smoking, 2) a good family pedigree with available DNA, and 3) a family history of bronchiectasis and/or occurrence of airways disease in a sibling. Classic CF, PCD and immune deficiency were ruled out, based on the tests described above. Alpha-1 antiprotease deficiency work up was negative and none of the patients were tobacco users or smokers.

  Study phs000518

• Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute

  Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000179 COPDGene_v6 Cohort. phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno

  Study phs000179

• University of Michigan Clinical Sequencing Exploratory Research (CSER)

  Overview. The personalization of therapy for cancer will require molecular characterization of unique and shared genetic aberrations. In particular, patients who have a sarcoma or other rare cancers and are candidates for clinical trials could potentially benefit by identifying eligibility for "targeted" drugs based on the "actionable" genes in their specific tumor. Growing technological advances in genomic sequencing has now made it possible to consider the use of sequence data in a clinical setting. For instance, comprehensive testing that includes whole exome and transcriptome sequencing may identify biomarkers for predictive or prognostic purposes and thereby inform treatment choices and prevention strategies. Thus, the translation of high throughput next generation sequencing would support a "personalized" strategy for cancer. However, the translation of clinical sequencing bears unique challenges including identifying patients who could benefit, developing informed consent and human subjects protections, outlining measurable outcomes, interpreting what results should be reported and validated, and how results should be reported. In addition, we know very little about how patients and clinicians will respond to the potentially confusing and overwhelming amount of information generated by genomic sequencing, and we lack model processes for clinically evaluating and presenting these data. For the promise of our innovative biotechnologies to be realized, "translational genomics" research that evaluates genomic applications within real-world clinical settings will be required. This proposal brings together expertise at the University of Michigan including clinical oncology, cancer genetics, genomic science/bioinformatics, clinical pathology, social and behavioral sciences, and bioethics in order to implement this clinical cancer sequencing project. Three integrated Projects have the following themes: Project 1) "Clinical Genomic Study" will identify patients with a rare cancer (i.e., 15 out of 100,000 individuals per year) who are eligible for clinical trials, consent them to the study, obtain biospecimens (tumor tissue, germline tissue), store clinical data, and assemble a multi-disciplinary Sequencing Tumor Board to deliberate on return of actionable or incidental genomic results; Project 2) "Sequencing &#38; Analysis" will process biospecimens and perform comprehensive sequencing and analysis of tumors to identify point mutations, copy number changes, rearrangements/gene fusions, and aberrant gene expression; Project 3) "Ethics &#38; Psychosocial Analysis" will observe the expert review process for evaluating sequence results and will examine the clinician and patient response to the informed consent process, delivery of genomic sequence results, and use of genomic results.

  Study phs000673

• Whole Blood Transcriptomics of Patients With Melioidosis

  Melioidosis is a neglected tropical infection caused by the Gram negative bacterium Burkholderia pseudomallei that is associated with high mortality rates in southeast Asia. The goal of this study was to a) identify human blood leukocyte transcriptomic features and pathways specific to melioidosis (vs other etiologies of infection), b) identify transcriptomic features and pathways specific to fatal melioidosis, and c) identify transcriptomic predictors of death in patients with melioidosis. This study used clinical data and whole blood leukocyte samples from a subset of participants in the Ubon Sepsis Study, a prospective single-center cohort study conducted at Sunpasitthiprasong Hospital, Ubon Ratchathani, Thailand between 2013 and 2017. Participants in the Ubon Sepsis Study had suspected or documented infection with accompanying systemic manifestations of infection and were enrolled, with blood sampling, within 24 hours of admission to the study hospital. Enrolled patients were followed over time and vital status was determined at 28 days after enrollment. The subset of participants from the parent Ubon Sepsis Study cohort selected for this study was comprised of 164 patients with melioidosis (defined as having a culture of clinical sample positive for B. pseudomallei), 35 patients with Gram negative bacteremia due to either Escherichia coli or Klebsiella pneumoniae, 16 patients with Gram positive bacteremia due to Staphylococcus aureus, and 19 patients who had negative blood cultures and no clinical sample culture-positive for B. pseudomallei. Fifty uninfected control patients with or without diabetes were recruited from the outpatient department and blood donation center at Udon Thani hospital, Udon Thani, Thailand from 2018 to 2019. Blood was collected at the time of enrollment in Tempus Blood RNA tubes. RNA was extracted using the Tempus Spin RNA Isolation kit. RNA sequencing (RNA-Seq) was performed at the University of Washington Northwest Genomics Center. Analysis was performed using a variety of statistical methods. The main finding of the study was that the transcriptomes of melioidosis patients, compared to patients with other infections, were characterized by upregulation of interferon signaling. The transcriptomes of patients with fatal melioidosis were notable for upregulation of inflammatory and type 2 immune responses and downregulation of genes related to T-cell function. A five-gene (EPHB1, SYCP2L, MERTK, IL5RA, and SPOCK1) predictive signature for death in melioidosis was developed.

  Study phs003724

• RNA_Seq_in_Patients_with_Primordial_Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.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 EGAS00001000283

• Plasma MicroRNA Signatures of Aging

  Background. MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally and show differential expression in various tissues with aging phenotypes. Detectable in circulation, extracellular microRNAs reflect (patho)physiological processes and hold promise as biomarkers for healthy aging and age-related diseases. This study aimed to explore plasma extracellular microRNAs as biological aging indicator and their associations with health outcomes using population-level data. Methods. We quantified plasma expression levels of 2,083 extracellular microRNAs using targeted RNA-sequencing in 2,684 participants from the population-based Rotterdam Study cohort. The training and test sets included 1,930 participants from the advanced-aged initial and second subcohort (RS-I/RS-II; median age: 70.6), while the validation set comprised 754 participants from the middle-aged fourth subcohort (RS-IV; median age: 53.5). Based on 591 microRNAs well-expressed in plasma, we examined differential expression of microRNAs with chronological age, PhenoAge –a composite score of age and nine multi-system blood biomarkers–, the frailty index, and mortality. Next, elastic net models were employed to construct composite microRNA-based aging biomarkers predicting chronological age (mirAge), PhenoAge (mirPA), frailty index (mirFI), and mortality (mirMort). The association of these aging biomarkers with different age-related health outcomes was assessed using Cox Proportional Hazard, linear regression, and logistic regression models in the test and validation sets. Results. We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (ntraining=1158, ntest=772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (nvalidation=754). Moreover, 227 miRNAs showed robust associations with PhenoAge, 61 with FI, and 16 with ten-year mortality independent of chronological age. Subsequently, we constructed four plasma microRNA-based aging biomarkers: mirAge with 108, mirPA with 153, mirFI with 81, and mirMort with 50 miRNAs. Elevated scores on these microRNA-based aging biomarkers were associated with unfavorable health outcomes, including lower subjective physical functioning and self-reported health and increased mortality and frailty risk, but not with first- or multi-morbidity. Overall, larger effect estimates were observed for mirPA, mirFI, and mirMort compared to mirAge. Conclusions. This study describes distinct plasma microRNA-aging signatures and introduces four microRNA-based aging biomarkers with potential to identify accelerated aging and age-related decline, providing insights into the intricate process of human aging.

  Study EGAS00001008117

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• EGA metadata schema

  EGA Schemas In this page, you will find information on how the European Genome-phenome Archive (EGA) manages its metadata standards using both XML Schema Definition (XSD) and JavaScript Object Notation (JSON) formats. If you are not sure what this means, you may want to explore our brief metadata introduction. This information may be of your interest if you are planning to learn more about how the EGA is built and how to wrap around it for other processes. Nevertheless, if you are a common user (e.g. submitter or requester), you would not have to worry about these schemas nor their format, since they are implemented in user-friendly ways for you. Metadata standards are rules that define how to format and structure data of metadata objects (i.e. entities), like EGA's samples or experiments in a consistent manner. These objects are the nodes of the metadata model of the EGA (Figure 1). Figure 1. Diagram of EGA's metadata model. The model's building blocks are objects (e.g. sample), which can reference each other (e.g. an experiment referencing the used samples). Once your files are uploaded, they can also be referenced by Runs and Analyses. The submission object is an object itself that compiles many others. At EGA, we inherit our metadata schemas from the European Nucleotide Archive (ENA), and we have expanded them to include bespoke objects such as "Policy", "Dataset", and "DAC" (Data Access Committee) for our specific use-case: handling sensitive human data. See below a list of all our metadata objects and some context for each. Metadata Object EGA accession Description Examples of metadata fields Study EGAS… Information about the study Study type, study title, study abstract… Sample EGAN… Information about the used samples in the experiment or analysis Taxon ID, scientific name, biological sex, phenotype… Experiment EGAX… Information about the performed experiment Used libraries, sequencing platform, reference to the used samples… Analysis EGAZ… Contains information about the analysis Type of analysis, used assembly, reference sequence… Run EGAR… The run holds information about the files containing the raw reads generated in a run of sequencing Platform, spot descriptor, raw file references… DAC EGAC… Contains information about the Data Access Committee (DAC) DAC contacts, contact emails… Policy EGAP… Contains the Data Access Agreement (DAA) and policy which its usage complies with Policy text, data use ontologies (DUO) codes… Dataset EGAD… Contains the collection of runs/analysis to be subject to controlled access Dataset type, compilation of Run's and Analysis' IDs There are two different sets of schemas, based on their formats, in which the EGA accepts metadata: XSDs (for XML files) and JSON Schemas (for JSON files). EGA's XML Schema Definition . When programmatic submissions are pushed through the European Bioinformatics Institute (EBI) system, XML format is used. The schemas that are applied for this format are defined in XML Schema Definition (XSD) files, which can be found at ENA's GitHub repository. You can find more information on how to validate and submit your data programmatically in our programmatic submission documentation. Furthermore, see at our GitHub repository some XML examples with either made-up values (similar to what you would submit) or descriptive values for each field (just for documentation). EGA's JSON Metadata Schemas . When programmatic submissions are pushed through the Centre for Genomic Regulation (CRG) system, JSON format specifications are used instead. See the full JSON specifications for further details. In conclusion, the EGA metadata schemas are crucial for maintaining the quality and consistency of submitted data. By understanding and following the rules outlined in these schemas, you can ensure that your submissions comply with the EGA's standards and contribute to a valuable and accessible genomic resource. Sample checklists Besides the standards in our schemas, we have another layer called Sample checklists. These are another system that the EGA inherits from ENA, and specifies what attributes are required or allowed for a sample object. The EGA uses these checklists to enforce that, for example, a sample object has the three mandatory attributes: subject ID, sex and phenotype of the individual the sample was taken from. When you submit to EGA, our checklist is automatically selected by default.

  Documentation submission/metadata/ega-schema

• Bone Microarchitecture

  Osteoporosis affects more than 28 million people in the United States and the lifetime risk for osteoporosis-related morbidity is higher than a woman's combined risk for breast cancer, endometrial cancer and ovarian cancer. Health care expenditures for osteoporotic patients in this country are currently nearly 13 billion dollars per annum and are predicted to increase markedly in the next decades due the aging of the population; therefore, it is important to understand the factors that contribute to bone strength and fracture risk. With the advent of skeletal imaging modalities such as high resolution peripheral quantitative computed tomography (HR-pQCT), it is now possible to study the genetics of more highly refined peripheral skeletal microarchitecture phenotypes. Because these refined phenotypes have not been measured in many cohort studies, this project was a collaborative effort to include almost all the existing data on HR-pQCT of the radius and tibia, and genetics from around the world. Cohorts involved in the discovery included: 1) Framingham Osteoporosis Study, 2) Mayo Clinic cohort; 3) Geneva Retirees cohort; 4) OFELY cohort from Lyon France; 5) STRAMBO cohort from Lyon France; 6) Swedish Male cohorts. Replication cohorts undergoing de novo genotyping include: 1) QUALYOR cohort from Lyon France; 2) CaMOS cohort from Canada. Other than the Framingham cohort and the Swedish male cohorts, all discovery cohorts underwent genome wide genotyping with the Affymetrix Axiom Biobank array that had common variants along with exome content based on the early findings from the Exome Sequencing Project. All genotype data from the discovery cohorts were then imputed using the Haplotype Reference Consortium reference panel. Variants for replication genotyping using the Kasp technology were selected based on novelty compared with previously identified loci using DXA phenotypes, minor allele frequency, underlying LD structure within a locus, and likelihood of a variant being functional as assessed using various algorithms for coding and non-coding variants.&nbsp; &nbsp;&nbsp;

  Study phs002102

• National Institute of General Medical Sciences (NIGMS) Human Genetic Cell Repository Human Variation Panels including 100 African-Americans (HD100AA), 100 Caucasians (HD100CAU), 100 Han People of Los Angeles (HD100CHI) and 100 Mexican American Community of Los Angeles (HD100MEX)

  The Human Genetic Cell Repository is sponsored by the National Institute of General Medical Sciences (NIGMS) with the mission of supplying scientists with the materials for accelerating disease gene discovery and functional studies. The resources available include highly-characterized, contaminant-free cell cultures and high quality, well-characterized DNA samples derived from these cultures, both subjected to rigorous quality control. The Repository was established in 1972 at Coriell and contains more than 9,500 cell lines, primarily fibroblasts and transformed lymphoblasts. The Repository has a major emphasis on inherited diseases and chromosomally aberrant cell lines. In addition, it contains a large collection dedicated to understanding human variation that includes samples from populations around the world, the CEPH collection, the Polymorphism Discovery Resource, Human Variation and many apparently healthy controls. The Human Variation collection provides cell lines and DNA samples from a variety of populations. The panels of African-Americans (HD100AA) and Caucasians (100CAU) used for this study are comprised of samples present in the Repository that were originally collected over the years from apparently healthy people to be used as "controls", for example, unaffected family members of persons with identified mono-genetic diseases. The samples for the Han people of Los Angeles (HD100CHI) and the Mexican American Community of Los Angeles (HD100MEX), however, were collected relatively recently from volunteers, identified as member of these communities, specifically for use in these panels. The Coriell Genotyping and Microarray Center in conjunction with the NIGMS repository used the Affymetrix Genome-Wide Human SNP 6.0 platform to genotype 400 samples from the NIGMS human variation panels. The populations genotyped included Americans of African, Caucasian, Mexican, and Han Chinese ancestry. The Affymetrix SNP 6.0 array detects approximately 940,000 SNPs and provides copy number information for more than 900,000 additional locations across the genome.

  Study phs000211

• Prediction of Trastuzumab Benefit in Adjuvant Breast Cancer: Gene Expression Profiling in NSABP B31

  Background National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-31 suggested the efficacy of adjuvant trastuzumab, even in HER2-negative breast cancer. This finding prompted us to develop a predictive model for degree of benefit from trastuzumab using archived tumor blocks from B-31. Methods Case subjects with tumor blocks were randomly divided into discovery (n = 588) and confirmation cohorts (n = 991). A predictive model was built from the discovery cohort through gene expression profiling of 462 genes with nCounter assay. A predefined cut point for the predictive model was tested in the confirmation cohort. Gene-by-treatment interaction was tested with Cox models, and correlations between variables were assessed with Spearman correlation. Principal component analysis was performed on the final set of selected genes. All statistical tests were two-sided. Results Eight predictive genes associated with HER2 (ERBB2, c17orf37, GRB7) or ER (ESR1, NAT1, GATA3, CA12, IGF1R) were selected for model building. Three-dimensional subset treatment effect pattern plot using two principal components of these genes was used to identify a subset with no benefit from trastuzumab, characterized by intermediate-level ERBB2 and high-level ESR1 mRNA expression. In the confirmation set, the predefined cut points for this model classified patients into three subsets with differential benefit from trastuzumab with hazard ratios of 1.58 (95% confidence interval [CI] = 0.67 to 3.69; P = .29; n = 100), 0.60 (95% CI = 0.41 to 0.89; P = .01; n = 449), and 0.28 (95% CI = 0.20 to 0.41; P &#60; .001; n = 442; P interaction between the model and trastuzumab &#60; .001). Conclusions We developed a gene expression-based predictive model for degree of benefit from trastuzumab and demostrated that HER2-negative tumors belong to the moderate benefit group, thus providing justification for testing trastuzumab in HER2-negative patients (NSABP B-47). ** Reprinted from J Natl Cancer Inst;2013;105:1782-1788 with permission from Oxford University Press.

  Study phs000826

• Genetic Epidemiology Network of Arteriopathy (GENOA)

  The Genetic Epidemiology Network of Arteriopathy (GENOA): GENOA is one of four research networks that form the NHLBI Family Blood Pressure Program (FBPP). From its inception in 1995, GENOA&#39;s long-term objective was to elucidate the genetics of hypertension and its arteriosclerotic target-organ damage, including both atherosclerotic (macrovascular) and arteriolosclerotic (microvascular) complications involving the heart, brain, kidneys, and peripheral arteries. Two GENOA cohorts were originally ascertained (1995-2000) through sibships in which at least 2 siblings had essential hypertension diagnosed prior to age 60 years. All siblings in the sibship were invited to participate, both normotensive and hypertensive. These include non-Hispanic White Americans from Rochester, MN (n =1583 at the 1st exam) and African Americans from Jackson, MS (N=1854 at the 1st exam). During the second exam (2000-2005), approximately 80% of participants were re-recruited. The GENOA data consists of biological samples (DNA, serum, urine) as well as demographic, anthropometric, environmental, clinical, biochemical, physiological, and genetic data for understanding the genetic predictors of diseases of the heart, brain, kidney, and peripheral arteries. Family Blood Pressure Program (FBPP): GENOA&#39;s parent program, the FBPP, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators began working together during the first funding cycle (1995-2000) and formalized this arrangement in the second cycle (2000-2005), creating a single confederation with program-wide and network-specific goals.

  Study phs000379

• The National Myelodysplastic Syndromes (MDS) Study

  Myelodysplastic syndromes (MDS) are the most common cause of adult bone marrow failure in the US and occur predominantly in people over the age of 60. Much of the morbidity and mortality for MDS is due to complications from low blood counts (e.g., infections and bleeding). MDS is caused by acquired DNA mutations that occur in a patient's blood cells as they grow older. Accumulating evidence suggests that MDS patients may traverse through a series of antecedent hematopoietic conditions defined by, i) clonal hematopoiesis (i.e., detectable somatic mutations in a person's blood cells) without low blood counts, a condition that affects up to 10% of individuals 70 years old and is termed Clonal Hematopoiesis of Indeterminate Potential (CHIP), or ii) clonal hematopoiesis with low blood counts (i.e., cytopenias) but no evidence of bone marrow dysplasia, termed Clonal Cytopenia of Undetermined Significance (CCUS). Nearly all CCUS patients will develop MDS over a ten year period, highlighting the prognostic importance of this disease. A better understanding of the genetic mutations, including non-coding and structural variants (SVs), occurring in CCUS and MDS could provide valuable insight into the natural history of MDS development. The NHLBI is conducting a longitudinal, observational study to create a standardized clinical dataset linked to a prospectively collected, consistently processed, and well-characterized biospecimen repository derived from approximately 1750 participants with suspected or newly diagnosed MDS or MDS/myeloproliferative neoplasm (MPN) overlap. These volunteers will donate biological specimens (like bone marrow and blood) and medical information, including details of their symptoms, how they perceive their quality of life, the treatments they receive, and what their doctor says about the severity of their illness over time. This information will be collected at pre-determined time points for the duration of the study. Study participants may be followed for life.

  Study phs002714

• McGill Epigenomics Mapping Centre

  The McGill Epigenomics Mapping Centre (EMC) and Data Coordination Centre (EDCC) were established in 2012 at the McGill University and Genome Quebec Innovation Centre (Montreal, Canada) to support large-scale human epigenome mapping for a broad spectrum of cell types and diseases. Previous epigenetic studies have provided profiles of specific chromatin marks in relation to basic biological processes, and future studies of molecular mechanisms must build upon these proofs-of-concept by integrating sequence-based variation with multiple levels of epigenetic and transcriptional regulation across the genome of human tissues and animal disease models. This project leverages the high-throughput sequencing infrastructure and expertise in genomics and transcriptomics at the McGill Innovation Centre to carry out this research. Controlled access to the data by collaborators and the greater scientific community is gained via a portal, which takes advantage of Compute Canada high-performance computing cluster resources to manage the large volume of data associated from the generation of reference epigenome maps. McGill University is one of two Canadian mapping and data coordination centres, the other based at the Michael Smith Genome Sciences Centre in Vancouver, British Columbia. The generation of comprehensive epigenome maps at McGill University is part of a larger international effort that is coordinated by the International Human Epigenome Consortium (IHEC), whose overall long-term objective is to determine the extent to which the epigenome shapes human populations over generations and in response to the environment. This project is funded under the Canadian Epigenetics, Environment, and Health Research Consortium (CEEHRC) by the Canadian Institutes of Health Research and by Genome Quebec, with additional support from Genome Canada. The computing and networking infrastructure, and part of the software development, are provided by Compute Canada and CANARIE.

  Study EGAS00001000995

• Whole exome and RNA sequencing of organoid samples derived from TRACERx patients

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of &gt;20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘hot’) and non-evading (‘cold’) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008092

• Same-day genomic and epigenomic diagnosis of brain tumors using realtime nanopore sequencing

  Molecular classification of cancer has entered clinical routine to inform diagnosis, prognosis and treatment decisions. At the same time, new tumor entities have been identified that cannot be defined histologically. For central nervous systems tumors, the current World Health Organization classification explicitly demands molecular testing, e.g. for 1p/19q- codeletion or IDH mutations, to make an integrated histomolecular diagnosis. However, a plethora of sophisticated technologies is currently needed to assess different genomic and epigenomic alterations and turnaround times are in the range of weeks, which makes standardized and widespread implementation difficult and hinders timely decision making. Here, we explored the potential of a pocket-size nanopore sequencing device for multimodal and rapid molecular diagnostics of cancer. Low-pass whole genome sequencing was used to simultaneously generate copy number (CN) and methylation profiles from native tumor DNA in the same sequencing run. Single nucleotide variants in IDH1, IDH2, TP53, H3F3A and the TERT promoter region were identified using deep amplicon sequencing. Nanopore sequencing yielded ~0.1X genome coverage within six hours and resulting CN and epigenetic profiles correlated well with matched microarray data. Diagnostically relevant alterations, such as 1p/19q codeletion, and focal amplifications could be recapitulated. Using ad hoc random forests, we could perform supervised pan-cancer classification to distinguish gliomas, medulloblastomas and brain metastases of different primary sites. Single nucleotide variants in IDH1, IDH2 and H3F3A were identified using deep amplicon sequencing within minutes of sequencing. Detection of TP53 and TERT promoter mutations shows that sequencing of entire genes and GC-rich regions is feasible. Nanopore sequencing allows same-day detection of structural variants, point mutations and methylation profiling using a single device with negligible capital cost. It outperforms hybridization-based and current sequencing technologies with respect to time-to diagnosis and required laboratory equipment and expertise, aiming to make precision medicine possible for every cancer patient, even in resource restricted settings.

  Study EGAS00001002213

• Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients

  Background: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. Methods: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~6x coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. Results: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and SCNAs. We further combined global and regional fragmentation pattern into a machine learning classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. Conclusion: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring.

  Study EGAS00001006490

• Proteomic Analysis of Non-Muscle Invasive and Muscle Invasive Bladder Cancer Highlights Distinct Subgroups With Metabolic, Matrisomal, and Immune Hallmarks

  We present the proteome biology of bladder cancer based on a cohort comprising treatment-naïve non-muscle invasive (NMIBC, N=17) and treatment-naïve muscle-invasive bladder cancer (MIBC, N=51), as well as neoadjuvant-treated MIBC (N=11); using formalin-fixed, paraffin-embedded samples and data-independent acquisition yielding &gt;8,000 protein identifications. The NMIBC proteome reveals two subgroups that represent cell adhesion or lipid metabolism biology. MIBC, compared to NMIBC, shows an altered metabolic proteome together with enrichment of extracellular matrix (ECM), immune response, and complement proteins; in line with three proteomic MIBC subgroups that represent ECM, metabolic, or immune signatures. The ECM and immune subgroups are enriched for markers of M2-like tumor-associated macrophages and dendritic cells, while markers for natural killer cells are exclusive for the ECM subgroup, and markers for cytotoxic T-cells are a hallmark of the immune subgroup. Infiltration of CD8+ PD1+ positive cytotoxic T cells correlated with PD-L1 expression of MIBC, as demonstrated by multiplex immunofluorescence analysis. The metabolic subgroup presents a comparably immune-depleted microenvironment. YAP1 signaling is particularly prominent in the ECM subgroup. The protein BSCL2 emerges as a prognostic marker for MIBC. We highlight increased endogenous proteolysis in MIBC alongside the upregulation of matrix metalloproteases exceeding the upregulation of their endogenous inhibitors. Genomic panel sequencing underlines prevalent FGFR3 mutations in NMIBC and prevalent TP53 mutations in MIBC, but a genomic underpinning of the MIBC subgroups remains elusive. Proteogenomic analysis yields protein-level evidence for more than 1,300 single amino acid variants. The proteomes of neoadjuvant-treated MIBC resembled treatment-naïve MIBC. Tumor-stroma interaction of MIBC was further investigated by proteomic analysis of patient-derived xenografts of MIBC. Our study adds to the proteome-level understanding of bladder cancer.

  Study EGAS00001007290

• Gene expression in CSF and blood of patients with pneumococcal meningitis

  Study EGAS00001003355

• Presence of bacterial infection in brains of patients with Huntington's disease

  Dac EGAC00001001222

• DAC for study Exon resequencing in patients with Brugada syndrome

  Dac EGAC00001000006

• DAC for study Population Structure and Genetic Diversity in Argentinean populations

  Dac EGAC00001000426

• DAC for genome-wide association study of prognosis in Crohn's disease

  Dac EGAC00001000568

• Identification of fungal species in brain of AD patients by NGS

  Dac EGAC00001000593