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• Synthetic - GDI synthetic data

  Synthetic - The Genomic Data Infrastructure (GDI) project is enabling access to genomic and related phenotypic and clinical data across Europe. It is doing this by establishing a federated, sustainable and secure infrastructure to access the data. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure the GDI project (funding: EC H2020 under grant agreement number 101081813) is acknowledged.

  Study EGAS50000000678

• Benchmark Dataset for Somatic Mutation Calling in Cell-Free DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Dataset EGAD50000001870

• Oral microbiome metagenomic sequencing - Human Phenotype Project (HPP)

  This study characterizes the oral microbiome of participants enrolled in the Weizmann Institute Human Phenotype Project (HPP), a longitudinal cohort study. Oral swab samples were collected and subjected to shallow whole-genome sequencing using the Gencove low-pass sequencing platform. Raw reads include residual human host sequences in addition to microbial sequences. The dataset comprises metagenomic FASTQ files from [N] participants. Data access is restricted in accordance with participant informed consent and Weizmann IRB approval

  Study EGAS50000001763

• Genomic Evolution of Breast Cancer Metastasis and Relapse

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

  Dataset EGAD00001002696

• Single cell transcriptomic data of human gut macrophages

  Cellular suspensions (∼15000 cells, with expected recovery of ∼7500 cells) of sorted CD45+ HLA-DR+ CD14+ macrophages from colonic mucosa and muscularis propria were loaded on the 10X Chromium Controller instrument (10X Genomics) according to the manufacturer’s protocol using the 10X GEMCode proprietary technology. All samples from individual patients were loaded in one batch. The Chromium Single Cell 3´ v2 Reagent kit (10X Genomics) was used to generate the cDNA and prepare the libraries, according to the manufacturer’s protocol. The libraries were then equimolarly pooled and sequenced on an Illumina NextSeq500 using HighOutput flow cells v2.5. A coverage of 400M reads per sample was targeted, in order to obtain 50 000 reads per cell. The raw data were then demultiplexed and processed with the Cell Ranger software (10X Genomics) v2.1.1.

  Dataset EGAD00001007765

• Disease specific alterations in the olfactory mucosa of patients with Alzheimer’s disease

  The sample AD_Library_1, AD_Library_2 and Control_Library were run on a Chromium Chip B with the Chromium Single Cell 3′ Library & Gel Bead Kit v3 kit (10x Genomics, CA, USA) . The 3’ gene expression libraries were sequenced at an approximate depth of 50,000 reads per cell using the NovaSeq 6000 S1 (Illumina, San Diego, CA, USA) flow cells. Cell Ranger v.3.0.2 was used to analyze the raw base call files. FASTQ files and raw gene-barcode matrices were generated and aligned human genome GRCh37 (hg19). The samples were integrated in R v.4.0.3 and generated Seurat objects, two related to AD samples and one to control samples, were analyzed using the Seurat package v.4.0.3 to perform downstream analysis, clustering of the cells and differential expression.

  Dataset EGAD00001008560

• Flexible and rapid validation of structural variants using adaptive sampling

  The goal of the study is to confirm and further characterize structural variants and complex genomic rearrangements using adaptive sampling with Oxford Nanopore Sequencing. Individuals with known structural variants were included in the study and the known rearrangement regions were targeted in the sequencing experiments. In addition to long-read coverage over the targeted regions (around 25X coverage), the rest of the genome is covered by short off-target reads (around 5X coverage).

  Study EGAS50000001279

• Follow_up_for_second_tier_signals_from_the_arcOGEN_GWAS

  The arcOGEN UK nationwide consortium has been funded by the arc to undertake a genome-wide association scan in osteoarthritis. GWA genotyping has been carried out at the Sanger on the illumina 610k array. This replication study was desinged to follow-up second-tier signals from the arcOGEN GWS in 25 SNPs (1Sequenom iPLEX) with p<5x10^-6 on 6000 additional UK OA and control samples.

  Study EGAS00001001017

• RNAseq data of polyA+ RNA from Leukocytes from 624 individuals of the ProgeNIA cohort.

  We sequenced the polyA+ fraction of the RNA of the leukocytes from 624 sardinian individuals with RNAseq. Prior to library preparation we added either ERCC ExFold RNA Spike-In. An average of 60M reads per samples with 51 bp paired-end reads were generated on a HiSeq 2000 (Illumina). Sequencing reads were then aligned using STAR-2.2.0c2 to the h37d5 reference genome supplemented with the ERCC spike-ins sequences. We further provided an exon-exon junction database that we generated from the GENCODE v14 annotation. In order to remove a contamination from a parallel experiment, we discarded any reads that mapped to the genomic regions of CBLB (chr3:105370773-105592330) and BCL11A (chr2:60672555-60784156). Filtered aligned reads (bam format) are shared.

  Dataset EGAD00001003102

• The Causes of Clonal Blood Cell Disorders Study - SCOR (2018-04-19)

  We will take a bone marrow aspirate and peripheral blood samples from a healthy patient aged around 60, and use flow cytometry to isolate 100 HSCs, 50 MEPs, and 50 GMPs. We will grow these up into colonies, then whole genome sequence each colony. Somatic mutations will act as a unique barcode for each clone. We will then design a panel for targeted resequencing of the mutations that we find. It will then be possible to look for these mutations in the peripheral blood over several years, to see the dynamics of how HSCs contribute to the peripheral blood in health. This dataset contains all the data available for this study on 2018-04-19.

  Dataset EGAD00001004086

• GAW16 Framingham and Simulated Data

  Important links to apply for individual-level data Genetic Analysis Workshop Instructions to Request Authorized Access Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Research Use Statement Questions regarding GAW16 should be directed to Vanessa Olmo at vanessa@business-endeavors.com. Problem 2: Description of the Framingham Heart Study In GAW16, we use data drawn from the Framingham Heart Study. The Framingham Heart Study — under the direction of National Heart, Lung, and Blood Institute; NHLBI — began in 1948 with the recruitment of adults from the town of Framingham, Massachusetts. At the time, little was known about the general causes of heart disease and stroke, but the death rates for cardiovascular disease (CVD) had been increasing steadily since the beginning of the 20th century and had become an American epidemic. The Framingham Heart Study is now conducted in collaboration with Boston University. The objective of the Framingham Heart Study was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Between 1948 and 1953 the researchers recruited 5,209 subjects (2,336 men and 2,873 women) between the ages of 29 and 62 from the town of Framingham, Massachusetts and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Subjects were recruited from lists of addresses recorded for the town. Two out of every three households were approached for participation in the study. While there was no intention to recruit families for family studies, the plan was to recruit all household members in the ages 30-60 within each house that was selected for study. Hence, many biologically related individuals were recruited, including 1644 spouse pairs. Since 1948, these participants have returned to the study every two years for a detailed medical history, physical examination, and laboratory tests. Now in 2008 at 60 years of follow up, there remain about 500 participants from this cohort. Between 1971 and 1975 the study enrolled a second-generation group — 5,124 of the original participants' children and the spouses of these children — to participate in similar examinations. 2,616 subjects are offspring of the original spouse pairs and 34 are stepchildren. A total of 898 offspring are children of cohort members where only one parent was a study participant and 1,576 are spouses of the offspring. The Offspring Cohort has been followed every four years through 2001 (except between Exams 1 and 2 with an intervening 8 years) using protocols similar to those used for study of the Original Cohort. Between 2002 and 2005 the study enrolled the third generation (Gen3) of the Framingham Heart Study - 4095 offspring of the second generation. None of their spouses were recruited. An additional 103 parents of this third generation, who were not recruited between 1971 and 1975, were also recruited at this time. The latter group is not included in the GAW16 data. With the recruitment of this third generation, the study has increasingly focused on genetic factors associated with the development of cardiovascular disease and its associated risk factors. To date, there is only one examination of this generation of participants. A description of the recruitment of this third generation and comparison with the earlier generations at their initial recruitment is presented in Splansky GL et al., 2007. Further information on the Study can be found at http://www.nhlbi.nih.gov/about/framingham/index.html. Genome-wide Dense SNP Scan in Framingham Heart Study Genetic studies did not begin in the FHS until the 1990s. In the late 1980s and through the 1990s DNA was extracted from blood samples of surviving FHS participants. In 2007, the FHS entered a new phase with the conduct of genotyping for the FHS SHARe (SNP Health Association Resource) project, for which dense SNP genotyping was performed using approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel) in 10,775 samples (some duplicates) from the three generations of subjects (including over 900 pedigrees). Affymetrix conducted all genotyping for the FHS SHARe project, using the 250K Sty, 250K Nsp, and the supplemental 50K platforms. Eighty-nine percent of the DNA samples were collected during the 1990s. To maximize the power of the study, we also extracted DNA from 1133 blood samples, drawn from subjects who had no DNA, to include in the SHARe project. These samples had been sitting in our refrigerators for some time, a few as far back as the 1970s. We refer to these DNA samples as the legacy samples. These samples had a higher failure rate in the genotyping process (40%) than the other eighty-nine percent (3%). Affymetrix invoked its own criteria for a sample to succeed in genotyping. All non-legacy samples must succeed on all three platforms, while legacy samples needed to pass on at least one platform. When a sample failed, additional attempts were made. Samples that repeatedly failed 2-4 times were called failures. Other samples failed due to issues of genotyped sex identification not matching our records or low SNP concordance among SNPs common across arrays or contamination. Eighty-nine percent of the legacy samples for which genotyping results are available passed all three platforms. The genotyping data from the 10,043 samples from 9354 subjects that passed the Affymetrix criteria were additionally checked for gender consistency and consistency with family structure, resulting in genotyping data for 9,274 participants in FHS SHARe. Genotype calls were made with the BRLMM algorithm. The SHARe database is housed at the National Center for Biotechnology Information database of genotypes and phenotypes (NCBI dbGaP) and contains all ~550,000 SNPs. This genome-wide dense SNP scan and a subset of phenotypes from the Framingham Heart Study are the focus of the Genetic Analysis Workshop 16. Further information on the specific variables in the Problem 2 dataset can be found by clicking on the Documents tab at the top of the page. Problem 3: Description of the Simulated Data Set The focus of this simulation is gene discovery in genome-wide association scans (GWAS). The Framingham Heart Study data set (distributed as "Problem 2") is the basis for the FHS* simulated data. The pedigree structures are derived from the data distributed for Problem 2, and we distribute an accompanying triplet file (triplet_sim) containing person ID, father ID, mother ID, to ensure the identical subjects, pedigrees, and singletons are used in the simulated data analysis. Consistent with standard practice, founders and singletons are designated as subjects with both fshare and mshare equal to zero (missing). The simulated data includes a total of 6,479 subjects with both phenotype and genotype data, in 942 pedigrees distributed among 3 generations and 188 singletons. Data inclusion is consistent with the subjects' consent for use by both for-profit and not-for-profit researchers. The genotypes for all Problem 3 replicates are fixed as measured and distributed for Problem 2 for both the genomewide scan and the additional candidate gene SNPs, for a total of approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel). Thus, to analyze the Problem 3 simulated data you also will need to download the Problem 2 genotypes. Note that there are slight discrepancies in counts between Problems 2 and 3 due to a change in consents between the two datasets. Several phenotypes that contribute to coronary heart disease (CHD) were simulated for all individuals with genotypes across three different time points, 10 years apart. All genotyped individuals have complete data; the effects of missing values can be investigated by user-specified missing value patterns. There are 200 longitudinal datasets created, based on the generating model, and each replication is found in a separate dataset. We suggest that if only one replication is to be analyzed, that it be replication 1 to enable more precise comparisons among analytical approaches. The 'shareid' will allow you to merge the simulated phenotype data with the Problem 2 genotype data, and reconstruction of the pedigrees using the distributed 'triplet_sim' file or for larger families' relationships with the triplet distributed with the Problem 2. The simulated data problem is further described in the associated readme file, and a data dictionary is provided defining all the variables. For disclosure of the generating model for these data, please contact Jean MacCluer at jean@sfbrgenetics.org.

  Study phs000128

• med-pchic-dac

  The data are accessible under the terms of the following Data Access Agreement that needs to be filled in, signed (by yourself and your institution’s official contact) and returned by email to med-pchic-dac@lists.cam.ac.uk

  Dac EGAC00001000523

• Sequence-Based Analysis of Human Breast Tumors

  The goal of this study is to study gene expression patterns in tumors, normal tissues, and cell lines.

  Study phs000676

• Identification of colorectal cancer susceptibility genes in Japanese

  We performed whole genome sequencing of 617 colorectal cancer patients registered in BioBank Japan to identify novel susceptibility genes.

  Study JGAS000699

• Whole-exome-sequencing in Frontotemporal dementia (FTD)

  To identify the genetic cause and modifiers of Frontotemporal dementia (FTD), we performed Whole-exome-sequencing of FTD patients.

  Study JGAS000374

• Identification of gastric cancer susceptibility genes in Japanese

  We performed whole genome sequencing of 256 gastric cancer patients registered in BioBank Japan to identify novel susceptibility genes.

  Study JGAS000698

• Identification of gastric cancer susceptibility genes in Japanese

  We performed whole genome sequencing of 2067 gastric cancer patients registered in BioBank Japan to identify novel susceptibility genes.

  Study JGAS000701

• Identification of diabetes mellitus susceptibility genes in Japanese

  We performed whole genome sequencing of 2162 diabetes mellitus patients registered in BioBank Japan to identify novel susceptibility genes.

  Study JGAS000700

• Sensitive gene analysis of hereditary cardiovascular disease

  This research aims to identify disease sensitive genes and their gene variants by genome analysis for hereditary cardiovascular diseases.

  Study JGAS000295

• Whole exome sequencing of colorectal cancer

  To elucidate immune status of solid tumors including gastrointenstinal cancer, we performed whole exome sequencing of colorectal cancer 7 patients.

  Study JGAS000279

• Identification of genetic mutations characteristic for recurrence of serous ovarian cancer.

  Establishment of novel therapeutic strategy to overcome intractable cancer by molecular profiling of serous ovarian cancer

  Study JGAS000104

• Spatial transcriptomics of human meningioma samples.

  We performed spatial transcriptomic profiling of human meningioma samples to map gene expression patterns within their native tissue architecture.

  Study EGAS50000001556

• BASIS_Genome_Validation_Study

  Bespoke validation experiments will be performed on ER+ Breast Cancer cases to confirm the presence of mutations found in whole genome sequencing.

  Study EGAS00001000403

• HCA_Gut_Paediatric_Hirschsprung_s_disease_Teichmann_Spatial_Managed_Access_

  This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease.

  Study EGAS00001007152

• Neuroblastoma Cell Line Circle-seq

  We generated Circle-seq data for 12 neuroblastoma cell lines to describe the landscape of extrachromosomal circular DNA in neuroblastoma.

  Study EGAS00001004796