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• Keratinocyte CRISPR screens (2019-08-14)

  Immortalised HaCaT keratinocytes were transduced with Cas9 and the CRISPR-KO v1.1 genome-wide gRNA library. The gRNA library was prepared from genomic DNA isolated 14 days post library transduction. gRNA representation will be compared to the original CRISPR-KO v1.1 library to reveal genes essential for HaCaT survival and growth. . This dataset contains all the data available for this study on 2019-08-14.

  Dataset EGAD00001005252

• NHLBI TOPMed - NHGRI CCDG: Genes-Environments and Admixture in Latino Asthmatics (GALA II)

  This is a case-only pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. Comprehensive phenotypic data for GALAII study participants are available through dbGaP phs001180.

  Study phs000920

• Human breast transcriptome analysis

  Obesity is a risk factor for the development of post-menopausal breast cancer and is associated with a worse breast cancer prognosis. Here we carried out transcriptome profiling on nontumorous breast tissue to define the molecular changes that occur related to excess body fat and adipose inflammation. A second goal was to determine if blood biomarkers reflect molecular changes in the breast. Increases in a variety of pathways linked to tumor development and progression were found. Moreover, increased expression of several drug targets including aromatase, the rate-limiting enzyme for estrogen biosynthesis, and PD-1 was observed. Various blood biomarkers that are associated with either elevated risk of breast cancer or worse prognosis were altered and correlated with molecular changes in the breast. Collectively, this study helps to explain both the link between obesity and breast cancer and the utility of blood biomarkers for determining risk and prognosis.

  Study EGAS00001004665

• eMERGE: Genetics of Complex Pediatric Disorders from the Center for Applied Genomics

  The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP) with the primary goal of translating basic research findings to medical innovations. The mission of CAG is to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders. We aim to discover genetic causes for the most prevalent diseases of childhood including asthma, autism, diabetes, epilepsy, obesity, schizophrenia, pediatric cancer, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. The CAG is one of the world's largest genetics research programs in pediatrics, and the only center at a pediatric hospital to have established a large-scale biobank of genotyped samples. The electronic Medical Records and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org.

  Study phs001165

• Angelman, Rett, Prader-Willi Syndrome Consortium (ARP) Rett Syndrome Natural History Protocol

  This observational study will involve the comprehensive assessment of the clinical features of Rett syndrome with this Rare Diseases Clinical Research Network. A clinical database of 1350 individuals with Rett syndrome including MECP2 mutation status for the purpose of elaborating phenotype-genotype correlations will be established. Eligible participants will be enrolled in the natural history study for 11 years from the 4 clinic sites currently involved with Rett syndrome (BCM, GGC, and UAB, CHB) as well as from the several thousand registrants in the International Rett Syndrome Foundation registry who will be invited to the nearest consortium site involved in Rett syndrome. Potential participants are expected to have had determination of their MECP2 mutation status, but will not be excluded should no mutation be present. All individuals who meet criteria and are currently receiving care from study sites will be invited to participate (N>600). Additional participants will be invited through the assistance of the International Rett Syndrome Foundation (IRSF). All individuals with RS registered with IRSF will be invited to participate in this study via the IRSF website and the IRSF newsletter. Potential participants will be apprised of the participating study sites and invited to contact one of the sites based on feasibility of travel. Inasmuch as the enrollment goal of 1350 participants is 40% of the current IRSF registry, we believe this will be a representative sampling. Bias can certainly occur based on travel requirements, level of interest, and other factors. However, inclusion of such a large sample should minimize sampling bias. No travel expenses will be covered, so it is likely that participants will be those with geographic proximity to Houston, Greenwood, Birmingham, or Boston. From the sample pool described above, the aim is to conduct the observational longitudinal (natural history) study on up to 1350 participants with classic Rett syndrome and variant forms of Rett syndrome, that is, participants who fully meet the established clinical criteria for Rett syndrome and those who meet some but not all of these criteria. All participants expressing MECP2 mutations irrespective of phenotype will be eligible for enrollment. For each of the eight common genetic mutations as well as those with large scale deletions, the prevalence of the following RS characteristics will be estimated for each age category and overall: seizure presence and frequency, ambulation status, scoliosis, ECG abnormality, breathing irregularities while awake, feeding difficulties, growth as measured in percentiles from NCHS standards curves, the presence of osteopenia as evidenced by bone fracture, and the presence of gallbladder disease. Both incidence and prevalence estimates will be made using a combination of data obtained at the regularly scheduled clinical visits and that obtained from the medical history. Incidence estimates will be calculated using time-to-event analyses (e.g., Kaplan-Meier survival curves) with appropriate calculations of standard errors and 95% confidence intervals. Cox proportional hazard regression models will be used to allow control for other factors, and t-tests will be calculated on the coefficients themselves. Appropriate transformations on explanatory variables will be used as deemed necessary in Cox models. Prevalence estimates will be calculated from estimates of proportions with exact confidence intervals. For a sample size of 275, the standard error of the estimate will not exceed 0.03 (3%) and for a sample size of 60, the standard error of the estimate will not exceed 0.06 (6%).

  Study phs000574

• Single cell sequencing data of PBMC and CSF from a cohort of Multiple Sclerosis patients and other neurological disease controls

  Neuroinflammation is often characterised by immune cell infiltrates in the cerebrospinal fluid (CSF). Here we apply single-cell RNA sequencing to explore the functional characteristics of these cells in patients with various inflammatory, infectious and non-inflammatory neurological disorders. We show that CSF is distinct from the peripheral blood in terms of both cellular composition and gene expression. We report that the cellular and transcriptional landscape of CSF is altered in neuroinflammation, but is strikingly similar across different neuroinflammatory disorders. We find clonal expansion of CSF B and T cells in all disorders but most pronounced in inflammatory diseases, and we functionally characterise the transcriptional features of these cells. Finally, we explore the genetic control of gene expression in CSF lymphocytes. Our results highlight the common features of immune cells in the CSF compartment across diverse neurological diseases and may help to identify new targets for drug development or repurposing in Multiple Sclerosis.

  Study EGAS50000000739

• Inherited Defect in ST6GalNAc1 Reveals Roles of Sialylation in Intestinal Homeostasis

  We have conducted a study of patients with unique mutations in the gene ST6GALNAC1 that encodes the protein ST6GALNAC1 (ST6). Exome sequencing was used to screen worldwide inflammatory bowel disease cohorts, which identified human loss of function mutations of ST6 in individual patients. The affected patients had very early onset (< 6 years old) inflammatory bowel disease. A comprehensive investigation of these gene mutations through in vivo and in vitro experiments revealed that decreased sialylation caused defective mucus proteins and congenital inflammatory bowel disease.

  Study phs002598

• New England-Based Case-Control Study of Ovarian Cancer

  The case-control data provided to dbGaP were collected under NCI grant number CA54419 which had 3 enrollment phases: I (1992-1997), II (1998-2002) and III (2003-2008). Altogether, CA54419 funded 15 years of data and specimen collection, resulting in one of the longest running population based case-control studies of ovarian cancer. The study goal was to examine reproductive factors, lifestyle exposures, and genetic background in relation to ovarian cancer risk. The project recruited cases from Eastern Massachusetts and New Hampshire, and became known as the New England-based Case-Control study (NECC) of ovarian cancer. 3957 ovarian cancer cases diagnosed at ages 18-80 and residing in Eastern Massachusetts and New Hampshire were identified through tumor boards and registries. Of these, 3083 (78%) were eligible and among those eligible, 2203 (71%) were enrolled. After excluding 127 non-epithelial and 35 mixed mesodermal tumors, 2041 cases with epithelial tumors of ovarian, primary peritoneal, and fallopian tube origin, including borderline malignancies were included. On average, cases were interviewed 10 months after their diagnosis. A pathologist reviewed pathology reports and recorded histologic subtype, grade, and stage. Mixed ovarian cancers described as predominantly one type were classified as that type. Undifferentiated, transitional cell tumors, or mixed serous/transitional cell tumors were counted as serous. Other mixed epithelial, malignant Brenner, and unspecified epithelial tumors were classified as other. 2100 controls were identified through random digit dialing (RDD), driver-license lists, and town-resident lists. During the first funding phase from 1992 to 1997, 420 (72%) controls identified through RDD and 102 (51%) through town-resident lists agreed to participate. From 1998 to 2008, only town-resident lists were used to identify potential controls. 4366 controls were identified, of whom 1426 (33%) were ineligible if they had died, moved, or were seriously ill or if they did not have a working telephone, speak English, or have at least one ovary. Of eligible controls, 1362 (46%) declined to participate by phone or via 'opt-out' postcard and 1578 (54%) were enrolled. Controls were frequency matched to cases by 5-year age groups and region of residence. In all phases, after written informed consent, demographic information, reproductive and medical history, and habits were assessed by in-person or telephone interview (in a few instances). All of the questions were framed with respect to a reference date defined as 1 year before the diagnosis date for women in the case group and the date of interview for those in the control group. This study was approved by institutional review boards at Dana Farber Harvard Cancer Center and Dartmouth Medical Center.

  Study phs001034

• Reference epigenomes generated as part of the International Human Epigenomics Consortium (IHEC)

  The Centre for Epigenome Mapping Technologies (CEMT) is an epigenome sequencing platform funded by the Canadian Institutes of Health Research (CIHR) and Genome BC as part of the Canadian Epigenetics, Environment and Health Research Consortium (CEEHRC). CEMT aims to produce 100 human reference epigenomes, each comprising the following datasets: whole genome; whole genome bisulfite and oxidative bisulfite; transcriptome; microRNA; and chromatin immunoprecipitation (ChIP)-seq for the core chromatin marks (H3K4me1, H3K4me3, H3K9me3, H3K27me3, H3K36me3, and H3K27ac).CEEHRC is a full member of the International Human Epigenomics Consortium (IHEC), which aims to coordinate the production of 1,000 reference maps of human epigenomes for key cellular states relevant to health and diseases. As such, all datasets submitted by the CEMT platform conform to IHEC assay standards and metadata guidelines.

  Study EGAS00001000552

• RNA_seq_of_Toxoplasma_gondii_response_in_human_macrophages

  Toxoplasmosis is a zoonotic disease caused by a ubiquitous protozoan parasite called Toxoplasma gondii, which caninfect all mammal and bird species throughout the world. seroprevalence varies widely between countries. Studieshave estimated that between 7-34% of people in the UK have been infected with T. gondii. The vast majority of thesepeople will not have noticed any symptoms, however about 10% of people develop a mild to moderate self limitingflu-like illness. Following the acute active stage of the infection the parasite persists in the body in the form of cysts,particularly in heart and skeletal muscle and nervous system tissues, for many years, and usually for life. Inimmunocompetent persons these cysts do not pose a health risk. We will use RNA-seq to quantify the transcriptionalresponse of macrophages to T gondii infection.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 EGAS00001001708

• Genetic Basis of Breast Cancer Resistance in BRCA1 Mutation Carrier

  Our study addressed a specific question in NCI RFA-CA-12-022: "What underlying causal events - e.g., genetic, epigenetic, biologic, behavioral, or environmental - allow certain individuals to survive beyond the expected limits of otherwise highly lethal cancers?". A germline mutation in BRCA1 (BRCA1+) is the most penetrant genetic predisposition for breast cancer. Nevertheless, a portion of BRCA1+ carriers does not develop breast cancer in their lifetime, suggesting that the genetic predisposition can be antagonized by resistant factors. BRCA1+ was inherited from an ancestor of the carrier family thousand years ago. We hypothesize that evolution could select certain genetic components to suppress oncogenesis caused by the predisposition. We compared germline variants in all genes in 27 pairs of breast cancer-unaffected and -affected BRCA1+ carriers, each pair inherited the same BRCA1+. We identified 12 deleterious variants enriched in breast cancer-unaffected carriers, all are common variants. A variant rs3735400 is located in ANLN, a cytokinesis-essential gene. Overexpression of variant-containing ANLN and suppressed expression of endogenous ANLN decrease ANLN nuclear localization and delay cell growth. Our findings suggest that common variants can be selected to resist oncogenesis imposed by BRCA1+.

  Study phs001243

• Whole genome sequencing with linked reads of pediatric glioblastoma samples

  Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand mechanisms of tumor evolution in this cancer, we performed whole genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of non-synonymous single nucleotide variants being shared in diagnostic-recurrent pairs. In order to track the origins of the mutational events we observed in pGBM, we generated whole genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) arose de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. Interestingly, radiation and anti-mitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, since slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and to accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM.

  Study EGAS00001003432

• Cohort A spatial transcriptomics sequencing

  Cohort A includes glioma tumors of varied grading and pathology from male and female individuals. Fresh frozen glioma tissues for each sample in cohort A were analyzed with the 10X Genomics Visium Spatial Gene Expression protocol. Processed data is available on the NCBI Gene Expression Omnibus database with accession GSE242352.

  Study EGAS50000000954

• Cohort B spatial transcriptomics sequencing

  Cohort B includes IDH-wild type, EGFR amplified, surgically derived glioblastoma tissue samples from male and female individuals. FFPE tissues for each sample in cohort B were analyzed with the 10X Genomics Visium CytAssist protocol. Processed data is available on the NCBI Gene Expression Omnibus database with accession GSE242352.

  Study EGAS50000000956

• Post-zygotic germline mutations in sperm

  These data from sperm were generated to demonstrate detection of post-zygotic mutations in the male germline. 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 please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001700

• Family Investigation of Nephropathy and Diabetes (FIND) Study

  The Family Investigation of Nephropathy and Diabetes (FIND) is a multicenter study designed to identify genetic determinants of diabetic kidney disease. Study subjects were recruited from eleven centers and in many ethnic groups throughout the United States. A genome-wide association study (GWAS) was conducted with the Affymetrix 6.0 chip. Subjects (index cases) with diabetes and kidney disease were initially recruited, and their parents and siblings were invited to participate. Genetic material from these participants was used to genotype markers throughout the genome. For association-based testing, a case-control design was implemented with study subjects selected primarily from the index cases of the families. Unrelated controls were selected from families where a case was not already selected. Several study sites also contributed non-FIND subjects, both cases and controls (consent forms for the release of FIND and non-FIND subjects/samples are included in this dbGaP release). Cases were selected if they met study criteria for diabetic nephropathy or met inclusion criteria based on elevated serum creatinine levels and abnormal urine protein excretion. Similarly, controls were long-term diabetics with otherwise normal kidney function. See inclusion/exclusion criteria section for a detailed description for the FIND study as a whole and this GWAS. The goal of the FIND study is to identify genes that influence susceptibility to diabetic kidney disease, leading to a better understanding of how kidney disease develops. In the long run, this may lead to improved treatment and prevention of diabetic kidney disease.

  Study phs000333

• MYO5B mutations in Pheochromocytoma/Paraganglioma promote cancer progression

  Identification of additional cancer-associated genes and secondary mutations driving the metastatic progression in pheochromocytoma and paraganglioma (PPGL) is important. We recently reported novel recurrent nonsynonymous mutations in the MYO5B gene in metastatic PPGL. Here, we explored the functional impact of these MYO5B mutations, and analyzed MYO5B expression in primary PPGL tumor cases in relation to mutation status.Immunohistochemistry and mRNA expression analysis in 30 primary PPGL tumors revealed an increased MYO5B expression in metastatic compared to non-metastatic tumor cases. In addition, subcellular localization of MYO5B protein was altered from cytoplasmatic to membranous in some metastatic tumors, and the strongest and most abnormal expression pattern was observed in a PGL case harboring a MYO5B:p.G1611S mutation. Mutation analysis of additional PPGL tumors revealed additional, and hence recurrent, mutations in the paralog MYO5A. Three missense mutations in MYO5B were functionally studied using site directed mutagenesis and stable transfection into human neuroblastoma cells (SK-N-AS) and embryonic kidney cells (HEK293 cell line). Functional analysis of the mutants verified a significant increased proliferation rate in all MYO5B mutated clones (p.L587P, p.G1611S, and p.R1641C). The two somatically derived mutations p.L587P and p.G1611S were also found to increase the migration rate, and all three mutants affected intracellular transport by increased transferrin uptake. Downstream expression analysis of MYO5B mutants demonstrated a transcriptional activation of genes involved in glucose metabolism, proliferation, homeostasis, and migration. Our study validates the functional role of novel MYO5B mutations in proliferation and migration, and suggest the MYO5-pathway to be involved the malignant progression of PPGL tumors.

  Study EGAS00001003991

• Clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancers defined by genomic analysis

  Ductal Carcinoma In Situ (DCIS) is the most common form of pre-invasive breast cancer and despite treatment a small fraction (5-10%) of DCIS patients present with invasive disease many years later. A fundamental biologic question is whether the invasive disease recurring in the same breast is established by tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial pure DCIS lesion and paired invasive recurrent tumors in 95 patients together with single cell DNA sequencing in a subset of cases. Our data shows that in 75% the invasive recurrence was clonally related to the initial DCIS, suggesting that the tumor cells were not eliminated during the initial treatment with surgery +/- radiotherapy. Surprisingly however, 18% were clonally unrelated to the DCIS, representing new independent lineages, and 7% of cases were ambiguous. Our findings show that although DCIS is often the precursor of invasive recurrence, a significant fraction of invasive recurrences are unrelated to the initial DCIS. This knowledge is essential for accurate risk evaluation of DCIS treatment de-escalation strategies and the identification of predictive biomarkers.

  Study EGAS00001005784

• Clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancers defined by genomic analysis

  Ductal Carcinoma In Situ (DCIS) is the most common form of pre-invasive breast cancer and despite treatment a small fraction (5-10%) of DCIS patients present with invasive disease many years later. A fundamental biologic question is whether the invasive disease recurring in the same breast is established by tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial pure DCIS lesion and paired invasive recurrent tumors in 95 patients together with single cell DNA sequencing in a subset of cases. Our data shows that in 75% the invasive recurrence was clonally related to the initial DCIS, suggesting that the tumor cells were not eliminated during the initial treatment with surgery +/- radiotherapy. Surprisingly however, 18% were clonally unrelated to the DCIS, representing new independent lineages, and 7% of cases were ambiguous. Our findings show that although DCIS is often the precursor of invasive recurrence, a significant fraction of invasive recurrences are unrelated to the initial DCIS. This knowledge is essential for accurate risk evaluation of DCIS treatment de-escalation strategies and the identification of predictive biomarkers.

  Study EGAS00001006306

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

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

  Study EGAS00001007767

• NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI)

  The Cancer Model Development Center (CMDC) project is part of the Human Cancer Model Initiative (HCMI) and is managed by the Office of Cancer Genomics within the Center for Cancer Genomics at the National Cancer Institute (NCI). The goal of the HCMI is to generate approximately 1000 novel human "next generation" tumor-derived models as a community resource. The models aim to faithfully recapitulate the cellular complexity and heterogeneity of human tumors. The CMDCs are tasked by the NCI with producing a proportion of the cancer models. Wellcome Sanger Institute (WSI) is a contributing member of the HCMI. Models developed by HCMI are being derived from a number of tumor types and subtypes (see below), including rare adult, pediatric and understudied cancers. The number of models and the clinical sites from which patient samples are acquired is increasing. Normal tissue, originating tumor, and tumor-derived models are sequenced. The next generation cancer models are associated with rich clinical and genomic data through the NCI Genomic Data Commons for all researchers to advance cancer research. The CMDC and HCMI models will serve as excellent tools in research to provide insight into the pathways that influence tumor growth and progression, how tumors respond to therapy, etc. Ultimately, the data generated using these models will support the development of personalized oncology. There is a delay between registered IDs and model availability. The current model count is found in The HCMI Searchable Catalog which is updated when new models are available for distribution to the research community.

  Study phs001486

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• Distribution of data using Live Distribution

  Live Distribution Welcome to the documentation for using the Live Distribution feature for distributing data files securely through the EGA platform. This guide will walk you through the process of downloading encrypted files and decrypting them using Crypt4GH. Please follow the steps below to ensure a smooth experience. Before Downloading Create an EGA user. Make sure that you have the permissions to download the dataset of interest. In case you don’t have access, request access to the dataset. Add your Crypt4GH-compatible public key to your EGA account. Please allow a few hours for your public key to be synced with your profile. Afterwards, you will be able to connect to your EGA outbox using the SFTP protocol. Download Graphical User Interface (GUI) You can use any GUI that supports SFTP connections, such as FileZilla, an open-source FTP client. For Filezilla as your GUI, follow these steps to download files: Open FileZilla and access Site Manager (File > Site Manager). Create a new connection with the following settings (Figure 1): Protocol: SFTP - SSH File Transfer Protocol Host: __EGA_OUTBOX_DOMAIN__ Logon Type: Key file User: your EGA username Key file: path/to/your/private_key Figure 1: Process of establishing a new connection to __EGA_OUTBOX_DOMAIN__ using a key file as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the EGA outbox, ensuring seamless data transfers. Click Connect to access your Outbox. This folder serves as your storage space within the EGA cloud, containing files accessible for download in a secure way. Browse the remote directory on the right side of the FileZilla screen. Select the files you wish to download, right-click, and choose Download (Figure 2). Figure 2: Step-by-step process of manually downñoad files from __EGA_OUTBOX_DOMAIN__ using FileZilla, with FileZilla version 3.52.2 operating on IOS v11.2.3. The figure demonstrates how users can downñoad data from the EGA outbox to their local storage by following the depicted steps SFTP command line You can also use the SFTP command line to securely download files from the EGA Outbox. Using SFTP command line client in Linux/Unix Open a terminal window Enter the following command to connect: sftp username@hostname Enter your EGA password To see a list of available sftp commands type help sftp> put – Upload file sftp> get – Download file sftp> cd path – Change remote directory to ‘path’ sftp> pwd – Display remote working directory sftp> lcd path – Change the local directory to ‘path’ sftp> lpwd – Display local working directory sftp> ls – Display the contents of the remote working directory sftp> lls – Display the contents of the local working directory Type get command to download files. For example: get encrypted_file.c4gh Use the bye command to close the connection (SFTP session). Convenient SSH settings Include the following settings in your SSH config file, located in ~/.ssh/config Host __EGA_OUTBOX_DOMAIN__ EGA-outbox hostname __EGA_OUTBOX_DOMAIN__ User username IdentityFile path/to/the/private/key Replace username and path/to/the/private/key with the appropriate settings, and you will be able to connect to the __EGA_OUTBOX_DOMAIN__ simply using sftp EGA-outbox. How to decrypt Files archived at the EGA are encrypted based on Crypt4GH. Hence, to decrypt the files you need to install Crypt4GH. You can install a python implementation of it, with pip install crypt4gh or directly from the Github repository pip install git+https://github.com/EGA-archive/crypt4gh.git After installing Crypt4GH, decrypt files using the following command: crypt4gh decrypt --sk /path/private/key < encrypted_file.c4gh > decrypted_filename The command reads the encrypted file from stdin (with <) and output the decrypted version to stdout (with >). Replace encrypted_file.c4gh and decrypted_filename with the appropriate filenames but make sure to not use the same filename for both reading and writing because your SHELL would then truncate both files before you even read or write. Frequently Asked Questions What username should I use to log in to my outbox? The authentication process for logging in to the EGA website, as well as accessing your inbox and outbox, requires the use of your username, not your email address. Therefore, if you registered a username different from your email address when creating your EGA account, you must use that username to log in. If you have forgotten your registered username, please, contact our Helpdesk team for assistance. I see that some files in my dataset have 'unavailable' as extension. What should I do? Within your Outbox, you'll find a list of all the datasets available for download. Occasionally, certain files may be marked as "unavailable". These unavailable files can be identified by the "unavailable" extension added to their filenames (e.g. filename.fastq.gz.unavailable.c4gh). If you encounter an unavailable file that you need, please reach out to our Helpdesk. We'll promptly work on making the file accessible for download as soon as possible. Specific to using keys Can I access one EGA account from different devices? Yes, you can access your account from different devices by linking several public keys to your EGA account. Each device can generate a unique public-private key pair, and the corresponding public keys can be linked to the same account. This way, you can use different public keys on different devices and still have access to the same account and data. I have several keys and I don't remember which one is which When generating SSH keys, it's a good practice to add a comment using the -C flag. This will allow you to add a descriptive tag to your key, making it easier to identify later on. Here's an example command that generates an SSH key with a comment: ssh-keygen -t ed25519 -C work-pass In this example, we're generating an ed25519 SSH key with the comment work-pass. Once you have multiple keys with different comments, you can use the comments to easily identify each key. To view the comments for your existing SSH keys, you can use the following command: ssh-keygen -l -f /path/to/key This will display the key fingerprint and the associated comment. By checking the comments, you should be able to identify which key is which. What if I can't find my SSH keys for uploading files with a key file, and how can I use new keys? If you can't find your SSH keys, don't worry - you can make new ones. To do this, open your terminal or command prompt and type a command to make a new SSH key. You can pick a name for the key, and choose a password to keep it safe. After making the key, you can add the new key to your account or server where you want to upload files using the key file. This usually involves copying and pasting the key's "public" (e.g. file.pub) part to the right place. If you lose track of the key again, just make a new one and add it again. Keep in mind that SSH keys belong to you and your computer, so if you switch computers or accounts, you'll need to make new keys. I don't want to type the passphrase every time I use the key. What can I do? You can use an ssh-agent to avoid typing the passphrase every time you use the key. An ssh-agent is a program that stores your private keys in memory and provides them to ssh when needed. You can add your key to the ssh-agent using the command ssh-add followed by the path to your key file.Here's an example of the steps to follow: Open a terminal window.Start the ssh-agent by typing the command eval $(ssh-agent).Add your key to the ssh-agent by typing the command ssh-add [key filepath]. For instance, if your key file is located in the home directory with the name mykey, the command will look like this: ssh-add ~/mykey After adding your, key to the ssh-agent, you should be able to use ssh without having to enter your passphrase every time. Can I use my password for authentication (without my private key)? If you prefer to use your username and password for authentication instead of your private key, you can still do so. When using a Graphical User Interface (GUI) such as FileZilla, you can select Ask for password as your Logon Type (Figure 3). This option will prompt you to enter your password when you click Connect, instead of using your private key. Figure 3: This option will prompt you to enter your password when you click "Connect", instead of using your private key. Figure 3: Process of establishing a new connection to __EGA_OUTBOX_DOMAIN__ using your password as the logon method in FileZilla. The figure showcases the FileZilla version 3.52.2 operating on IOS v11.2.3. By following the depicted steps, users can create a secure and efficient connection to the inbox, ensuring seamless data transfers. It's worth noting that using a password for authentication can be less secure than using an SSH key, as passwords can be more easily compromised through various means. However, if you choose to use your password for authentication, selecting "Ask for password" as your Logon Type is a good way to do so securely via a GUI. Why is it better to use my key and not my password? SSH keys for authentication is generally considered to be more secure and convenient than using passwords. SSH keys are more difficult to crack than passwords, and they can be restricted to specific users and machines, giving you more control over access. Once you set up your SSH keys, you can use them to authenticate quickly and easily, without having to enter a password every time. This makes automation of tasks, such as uploading encrypted files, much simpler. Additionally, SSH keys provide better logging, allowing you to keep track of who is accessing your systems and when. All in all, using SSH keys is a good practice for improving security and convenience in your authentication process.

  Documentation access/download/files/live-outbox

• Wisconsin Longitudinal Study on Aging

  The Wisconsin Longitudinal Study (WLS) is a long-term study of a random sample of men and women, who graduated from Wisconsin high schools in 1957, and their siblings. The WLS panel started out with a panel of 10,317 members from the class of 1957. Over time a second panel of 8,734 randomly selected siblings of the original graduate panel were recruited for the study. Of these combined panel members, 9,027 survived and contributed saliva for genetic analysis. Survey data were collected from the original respondents or their parents in 1957, 1964, 1975, 1992, 2004, and 2011, and from a selected sibling in 1977, 1994, 2005, and 2011. WLS data provide a detailed record of educational, social, psychological, economic, mental and physical health characteristics of a relatively homogeneous population that is almost entirely of Northern and Western European ancestry. Saliva was first collected in 2007-2008 by mail. Additional samples were collected in the course of home interviews that began in March 2010.

  Study phs001157

• Targeted resequencing of Cardiomyopathies associated genes

  In this study, we present the results of a custom “pan-cardiomyopathy panel” in a molecular screening of 38 unrelated patients, 16 affected by DCM, 14 by HCM, and 8 by ARVC. The panel was designed using the Design Studio Tool (Illumina, San Diego, CA,USA). Coding regions and intron–exon boundaries of 115 genes, known to be associated with 7 DCM, HCM, and ARVC as well as channelopathies, were selected for targeted gene enrichment. For genes with multiple transcripts, all exons included in transcripts expressed in cardiac muscle were considered in the gene panel design. Total DNA was extracted from peripheral blood samples using the Wizard Genomic DNA Purification Kit (Promega, Mannheim, Germany) according to the manufacturer’s instructions, quantified, and qualitatively checked using NanoDrop 2000c (Thermo Fisher Scientific, Waltham, MA, USA). Custom targeted gene enrichment and DNA library preparation were performed using the Nextera Capture Custom Enrichment kit (Illumina) according to the manufacturer’s instructions. Targeted regions were sequenced using the Illumina MiSeq platform, generating approximately two millions of 150-bp paired-end reads for each sample (Q30 ≥90%).

  Dataset EGAD00001003359

• Extramammary Paget Disease

  37 surgical samples were interrogated by WXS, and 50 formalin-fixed, paraffin-embedded samples were interrogated by target-seq. Agilent SureSelect XT kit and SureSelect Human Exon V6 were used to generate exome libraries. Agilent SureSelect XT low input kit and custom capture panel designed on SureDesign were used to generate target-seq libraries. All libraries were sequenced on Illumina HiSeq 2500 platform.

  Dataset EGAD00001006449

• Primary breast tumor heterogeneity through therapy

  We performed whole-exome sequencing on multiple regions (n=2-3) from four primary untreated breast tumors (n=1 HER2+, n=2 ER+/HER2-, n=1 triple-negative), as well as matched normal. We also performed whole-exome sequencing on one region from the pre-treatment diagnostic core biopsy and multiple regions (n=2-6) from the post-treatment surgical specimen for five HER2+ primary breast tumors, as well as matched normal; all were treated with combination chemotherapy and trastuzumab. Analysis of these specimens allows characterization of breast tumor heterogeneity and clonal evolution.

  Study EGAS00001003168

• Illumina ExomeChip genotyping data from the Cretan Greek isolate collection HELIC MANOLIS

  Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies. Here we have genotyped individuals from a Greek population isolate on the Illumina HumanExome Beadchip. The HELIC (Hellenic Isolated Cohorts) MANOLIS (Minoan Isolates) collection focuses on Anogia and surrounding Mylopotamos villages. Recruitment of this population-based sample was primarily carried out at the village medical centres. All individuals were older than 17 years and had to have at least one parent from the Mylopotamos area. www.helic.org **The data may not be used for population genetics analyses.**

  Study EGAS00001000630

• Whole genome bisufite sequencing of smoking and non-smoking mother-child pairsBisufite sequencing, RNA-seq and ChIP-Seq data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years.

  Whole-blood samples of 16 mother-child pairs with differing maternal smoking behaviour were bisulfite treated and sequenced with deep coverage to identify smoking-associated differentially methylated regions.RNA-sequencing and ChIP-sequencing of 4 chromatin marks complete the data set and allow for integrative analyses, functional region annotation and to study the impact of epigenetic changes on gene expression.Longitudinal data spanning several years provides the means to investigate the stability of observed differences of all data types.

  Study EGAS00001000455

• Illumina Human OmniExpress genotyping data from the Cretan Greek isolate collection HELIC MANOLIS

  Isolated populations can empower the identification of rare variation associated with complex traits through next generation association studies. Here we have genotyped individuals from a Greek population isolate on the Illumina Human OmniExpress BeadChip array. The HELIC (Hellenic Isolated Cohorts) MANOLIS (Minoan Isolates) collection focuses on Anogia and surrounding Mylopotamos villages. Recruitment of this population-based sample was primarily carried out at the village medical centres. All individuals were older than 17 years and had to have at least one parent from the Mylopotamos area. www.helic.org **The data may not be used for population genetics analyses**

  Study EGAS00001000687

• Patient tumour data (RNAseq, WGBS, ChIPseq, WGS)

  Content: 60 GB patient tumours and 4 normal brain samples combined in pairs by region (x2=8 total input samples). RNAseq: 1 lane per sample, total strand-specific rRNA-depleted (normal samples were combined = 2 lanes/samples per brain region). WGBS: 2 lanes per sample (normal samples were combined = 2 lanes/samples per brain region). ChIPseq (histone mark): a subset of 20 GB samples were profiled. For the same modification were multiplexed and sequenced on 4 lanes each (H3K27ac, H3K4me1) or a single lane (all others). WGS: used as matching input control for the 20 ChIPseq samples. Data type and technology: RNA-seq: PE 100bp sequenced on HiSeq2000. WGBS: PE 100bp sequenced on HiSeq2000/4000. ChIPseq: SE 50bp sequenced on HiSeq2000/4000. WGS: PE 150bp sequenced on HiSeq X.

  Dataset EGAD00001005492

• Genomic Data Archive From the Network for Pancreatic Organ Donors With Diabetes

  The Network for Pancreatic Organ Donors with Diabetes (nPOD) is the largest biorepository of human pancreata from organ donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, and islet autoantibody positive (AAb+)/pre-T1D. The mission of the nPOD is to distribute biospecimens and associated de-identified data/metadata to an international researcher network, and to promote the development of new treatments for these diabetes conditions. Here, we describe the release of high-parameter genotyping data for the nPOD cohort. Specifically, 372 subjects were genotyped using a customized precision medicine single nucleotide polymorphism (SNP) microarray (UFDIchip). These data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 subjects were queried for rare known and novel coding region variants via whole exome sequencing (WES). These data are now publicly available, enabling genotype-selected sample requests and the study of novel genotype : phenotype associations, ultimately to explain diabetes heterogeneity and inform precision medicine strategies to interrupt diabetes pathogenesis.

  Study phs002861

• Fixative optimisation study for BRITROC project

  The British Translational Research Ovarian Cancer Collaborative (BriTROC), spanning more than 10 centres across UK, is a prospective observational project focused on relapsed high-grade serous ovarian cancer (HGSOC). The first study, as a part of the project, is the Fixative optimisation study, which analyses the utility for next-generation sequencing of UMFIX samples compared to NBF-fixed and fresh frozen samples. Various DNA and sequencing quality analyses were performed to compare fixation methods in bulk tumour and biopsy samples.

  Study EGAS00001001433

• Whole Exome Sequencing of One Nuclear Family with Non-syndromic Sensorineural Hearing Loss

  Our goal is to find genes responsible for non-syndromic sensorineural hearing loss. Blood samples were collected from the JS6 family affected with hearing loss. The family is of Caribbean Hispanic ethnicity. Family JS6 consisted of two deaf siblings, JS6.001 (Male) and JS6.002 (Female) and healthy parents, JS6.100 (mother) and JS6.200 (father). The siblings had no other medical findings. Audiometry tests and Rinne and Weber tuning fork tests identified sensorineural hearing loss in the two siblings. We performed whole exome sequencing of the four individuals and identified a recessive mutation, p.(Arg186Trp), in the CIB2 gene in the two affected siblings. Both parents were unaffected carriers.

  Study phs000969

• WES of pleomorphic lung cancer

  Pulmonary pleomorphic carcinoma (PPC) is an aggressive and highly heterogeneous non-small-cell lung carcinoma whose underlying biology is still poorly understood. Forty-two tumor areas including 39 primary tumors and 3 metastases from 20 PPC patients were microdissected and the histologically distinct components were subjected to whole exome sequencing (WES) separately. Twist Human Core Exome + RefSeq + Mito-Panel kit (Twist Bioscience) was used for the whole exome capturing according to manufacturer’s guidelines. Paired-end 100-bp reads were generated on the Illumina NovaSeq 6000. After the sequencing, reads were aligned against the reference human genome GRCh38 using Burrows-Wheeler Aligner (BWA, v0.7.12)

  Dataset EGAD50000000453

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

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

  Study EGAS00001006139

• NHLBI TOPMed: Australian Familial Atrial Fibrillation Study

  In the Australian Familial AF Study, a cohort of probands with familial AF was recruited for genetics studies at the Victor Chang Cardiac Research Institute. Familial AF cases were identified from in-patient and out-patient populations at St. Vincent's Hospital and by referral from collaborating physicians throughout Australia. Study subjects underwent clinical evaluation with history, ECG and echocardiogram, and informed consent was obtained from all participants. 151 probands aged &lt;66 years at the time of diagnosis were included in this analysis. The control cohort was comprised of age- and sex-matched individuals (n=151) who had no history of cardiovascular disease. In the current TOPMed study, we have performed whole genome sequencing in European Ancestry cases with early-onset atrial fibrillation (defined as atrial fibrillation onset prior to 61 years).

  Study phs001435

• High-coverage whole exome sequence in non-TRU-type lung adenocarcinomas

  In order to elucidate the key genetic events in non-TRU-type lung cancer, we selected 43 non-TRU-type lung adenocarcinomas and performed a whole exome sequence and RNA-seq analysis using a next-generation sequencer. The results of the analysis identified mutations in TP53, KRAS and NKX2-1 as the top three significantly mutated genes, while the EGFR mutation was rare in this cohort. Eight NKX2-1 mutations (5 frameshift, 2 nonsense, and one missense) were identified, with one case harboring two distinct NKX2-1 mutations (missense and frameshift). All NKX2-1 mutants were transcriptionally inactive in reporter assays. Histologically, invasive mucinous adenocarcinomas accounted for most of the NKX2-1 mutations (5 cases), while 1 enteric and 1 acinar adenocarcinoma harbored the NKX2-1 mutation.

  Study JGAS000105

• Korean Young Age Diffuse Gastric Cancers

  The incidence of diffuse gastric cancers (DGC) remains steadily high, but relatively small numbers of DGCs have been evaluated with whole exome sequencing (WES). Clinicopathological features of DGC vary according to age, but the molecular basis for these variations is unclear. To identify genomic alteration in this unique subset of gastric cancers, whole exome and SNP6 analyses were performed using frozen cancer tissue. The same analyses were also performed using blood of the same patients.

  Study EGAS00001001711

• Myocardial Infarction Genetics Exome Sequencing Consortium: University of Lubeck

  MI cases were recruited from the German MI Family Study and the Angio-Lub study. Controls were recruited from the German MI Family Study and the Angio-Lub study. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina&#39;s ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000990

• Olink Explore Protein Expression

  Serum samples (DC, CRSsNP, CRSwNP, N-ERD, n=20 each) were subjected to the Olink Explore 3072 analysis including the following panels: Olink Explore 384 Cardiometabolic and Cardiometabolic II, Olink Explore 384 Inflammation and Inflammation II, Olink Explore 384 Neurology and Neurology II, Olink Explore Oncology and Oncology II. The latter had 4 failed samples. From the originally 2925 unique proteins determined, 84 proteins had missing values in all samples and were removed. Further 164 proteins had >50% of values below LOD across all four groups and were removed with remaining values below threshold adjusted to LOD. This data cleaning left 2695 unique assays (2677 unique proteins) in serum to be analysed. Additionally, six assays (LMOD1, IDO1, SCRIB, CXCL8, IL6, TNF) were measured four times each in different panel.

  Dataset EGAD50000001327

• 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

• Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET)

  STARNET is a genetics of RNA expression study of multiple disease-relevant tissues obtained from living patients with cardiovascular disease. Tissue samples are obtained from blood, atherosclerotic-lesion-free internal mammary artery (MAM) and atherosclerotic aortic root (AOR), subcutaneous fat (SF), visceral abdominal fat (VAF), skeletal muscle (SKLM), and liver (LIV) during open thorax surgery of 600 coronary artery disease (CAD) patients. All patients gave written informed consent. The inclusion criterion was eligibility for coronary artery by-pass graft (CABG) surgery. Patients with other severe systemic diseases, such as active systemic inflammatory disease or cancer, were excluded. The primary clinical end points were the SYNTAX score based on the extent of coronary atherosclerosis assessed from preoperative angiograms. The STARNET patients are Caucasians (31% females); 32% had diabetes, 75% had hypertension, and 67% had hyperlipidemia; and 33% had an MI before age 60. By New York Heart Association criteria, 45% were class I, 42% class II, 9% class III, and 1% class IV. TYPES AND RNA SEQUENCING: 566 DNA genotype and 3577 RNA-seq profiles from seven tissues from 600 STARNET CABG patients passed quality control (on average 511 RNA-seq profiles/tissue). DNA was genotyped with the OmniExpress Exome array (Illumina, ~900k SNPs) and imputed to a total of 14,098,063 DNA variant calls (6,245,505 with minor allele frequency &gt;5%). The STARNET subjects mainly overlap with Caucasian of Northern European (Finnish) descent. RNA sequencing was performed using the HighSeq2000 platform, poly-A (LIV, SKLM, VAF, SF and blood) and ribo-zero (AOR, MAM) protocols with 50-100 bp read lengths, single end to 15-30 million read depth.

  Study phs001203

• SECRETO Oral metagenome study

  The main goal of the project is to study the associations between the oral metagenome and young-onset cryptogenic ischemic stroke (CIS). The dataset includes information for n=329 participants who underwent saliva sampling. Participants for the SECRETO Oral study were enrolled between December 2013 and November 2019. Shotgun metagenomic sequencing was performed using the Illumina NovaSeq 6000 platform.

  Study EGAS00001007505

• Immunotesting cohort with RNA-seq data of melanoma samples

  This dataset contains RNA-seq raw data in fastq format from 9 melanoma samples. The samples are formalin-fixed paraffin-embedded (FFPE) treated. For target enrichment SureSelect XT Human All Exon V6 was used. The libraries were sequenced in paired-end mode (2 x 50 nt) on a NovaSeq6000 S2 flow cell.

  Dataset EGAD00001006783

• Single-cell RNA sequencing of blood immune cells before and after interleukin-2 immunotherapy

  Single-cell RNA sequencing of flow cytometry sorted human CD45+ immune cells from 3 systemic lupus erythematosus patients (SLE_002, SLE_004, and SLE_006) collected at baseline (day 0, before interleukin-2 immunotherpay) and day 5 (after 1 treatment cycle of interleukin-2 immunotherapy). Sorted immune cells were hash tagged and then stained with TotalSeq Human Universal Cocktail (Biolegend) before further processing for single-cell RNA sequencing using the 10X-Genomics platform. Samples from all 3 patients were pooled and loaded on 3 lanes of the chromium controller, resulting in 1 raw sequncing file for each lane.

  Dataset EGAD50000000662

• The Ultrasound Study of Tamoxifen

  The Ultrasound Study of Tamoxifen is a 12-month longitudinal study to describe volumetric breast density change over time among women with and without tamoxifen exposure. Women were enrolled at the Karmanos Cancer Institute and Henry Ford Health Systems in Detroit, Michigan between 2011-2014. Enrollment included women prescribed tamoxifen for clinical indication (n=82) and a comparison group of women frequency matched on age, race, and menopausal status (n=165). Whole breast ultrasound tomography (UST) scans were used to measure volume averaged sound speed (m/s) as a surrogate of volumetric breast density. Ultrasound tomography (UST) scans were completed at baseline prior to tamoxifen initiation and were repeated at 1-3 months, 4-6 months, and 12 months after tamoxifen initiation. For the comparison group, UST scans were completed at baseline and 12 months. Questionnaires were completed at each scan.

  Study phs003183

• IBD Whole Genome Sequencing (2019-04-01)

  We will sequence at 15X coverage the genomes of 1536 IBD patients. These samples are currently onsite at Sanger and made available for sequencing via our collaboration with the UK IBD Genetics consortium. 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/ . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004880

• Genome Diversity in Africa Project - GemCode libraries (2017-07-05)

  High depth whole genome sequencing from GemCode (10x Genomics) DNA libraries containing long range linkage information for one Baganda trio and one Baganda child (parent already sequenced at high depth). 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/ This dataset contains all the data available for this study on 2017-07-05.

  Dataset EGAD00001003426

• Oceanian and American population sequencing and phasing (2019-04-11)

  Whole-genome sequencing of human individuals from Polynesian and Native American populations, as well as 10x Genomics Chromium data from Polynesian, Native American and Aboriginal Australian populations, allowing for experimental phasing of haplotypes. 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 please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-04-11.

  Dataset EGAD00001004951