WGS data for cell lines and clinical samples
PALMO (Platform for Analyzing Longitudinal Multi-omics data) is a platform for analyzing longitudinal data from bulk as well as single cell. It allows to identify inter-, intra-donor variations in genes over longitudinal time points. The analysis can be done on bulk expression dataset without known cell type information or single cell with cell type or user defined groups. It allows to infer stable and variable features in a given donor and each cell type or a user defined group. The outlier analysis can be performed to identify technical/biological perturbed samples in a donor or a participant. Further, differential analysis can be performed to decipher time-wise changes in gene expression in a cell type. The data that is available in the dbGaP is the demo longitudinal samples used in the study, which includes hashed raw fastq files for single-cell RNA-sequencing (scRNA-seq) and non-hashed fastq files for single-cell ATAC-sequencing (scATAC) experiment.
Structural variants (SVs) involving enhancer hijacking can disrupt chromatin topologies to cause oncogene activation in cancer genomes, yet the molecular determinants for the transcriptional output of enhancer hijacking remain largely unknown. We developed a multimodal approach to integrate genome sequencing, chromosome conformation, and sequence-based deep learning for quantitative analysis of transcriptional effects and structural reorganization imposed by SVs in leukemic genomes. We identified candidate pathogenic SVs including recurrent t(5;14) translocations that cause the hijacking of BCL11B enhancers for oncogenic activation of TLX3-dependent transcriptional programs. By engineering patient-associated t(5;14) in isogenic leukemia cells, we uncovered an uncharacterized mechanism whereby DNA methylation serves as an epigenetic barrier to enhancer hijacking and loss of epigenetic barrier is a molecular determinant for the transcriptional output of pathogenic SVs. Hence, leveraging the epigenetic barriers of SV-mediated oncogenic programs may provide new opportunities to reprogram gene regulation as epigenetic therapies in human disease.
The Northern Ireland COhort for the Longitudinal study of Ageing (NICOLA) is a representative sample of ~8,500 people from across Northern Ireland. The study, which was set up in 2012, aims to understand what it is like to grow older in Northern Ireland. • NICOLA has a strong focus on molecular biomarkers so there is complementary genetic, epigenetic and transcriptomic data available for a subset of individuals. • We inherit much of our DNA from our parents while a small amount of this material changes as we get older. In NICOLA we have 551,839 directly genotyped and 18,148,478 imputed Single Nucleotide Polymorphisms (SNPs) currently available for 2969 participants. • Summary statistics for the association of these gene polymorphisms with ~30 phenotypes were generated. • Epigenetics provides a link between our inherited DNA and environmental influences from a person’s diet, medication and lifestyle. NICOLA has the epigenetic quality controlled profiles of 1984 individuals arising from variations in DNA methylation at 862,927 genetic sites.
EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.
CRISPR engineering of human T cells
Screening for human epigenetic variation at CpG islands
SNP data for Ovarian cancer PRS (cases)
The ICBP consortium is an international effort to investigate blood-pressure genetics. The consortium was formed by two parent consortia, the CHARGE-BP consortium (Cohorts for Heart and Aging Research in Genomic Epidemiology - blood pressure) and the GBPGEN consortium (Global Blood Pressure Genetics Consortium). In 2011 we performed genome-wide association analyses based on genome-wide SNPs imputed to HapMap for systolic and diastolic blood pressure (SBP and DBP) and mean arterial pressure and pulse pressure (MAP and PP). In 2016 we performed an analysis based on the Cardio-MetaboChip for SBP and DBP. All these datasets are available here, however, full association statistics including effect size directions, only under controlled access by dbGaP.
