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• Repertoire and clinical hierarchy of AR locus alterations in castration-resistant prostate cancer

  Somatic alterations to the androgen receptor (AR) gene are pivotal drivers of treatment resistance in metastatic castration-resistant prostate cancer (mCRPC), but their prevalence, clinical impact, and etiology remain incompletely understood. Here, we analyzed 3399 plasma cell-free DNA samples and 1988 leukocyte DNA samples from 1995 metastatic prostate cancer patients with matched clinical data and extensive AR locus coverage.

  Study EGAS50000001101

• De_novo_mutations_in_cell_free_foetal_DNA__cffDNA_

  This project is to develop and validate a method to detect de novo mutations in a foetal genome through deep sequencing of cell-free DNA from the plasma of pregnant women.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000322

• Whole-exome sequencing of intravascular large B-Cell lymphoma

  Intravascular large B-cell lymphoma (IVLBCL) is a unique form of diffuse large B-cell lymphoma (DLBCL) characterized by extranodal cell growth especially in small vessels without systemic lymphadenopathy. The limitation in obtaining sufficient tumor materials hampers understanding the molecular pathogenesis of IVLBCL. We performed whole-exome sequencing of IVLBCL using plasma-derived cell-free DNA (cfDNA) and patient-derived xenograft (PDX) samples.

  Study EGAS00001003970

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

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

  Dataset EGAD00001015535

• Tampere University Celiac Disease Research Data Access Committee

  This DAC will be used to reposit RNAseq data from intestinal biopsies of celiac disease patients on gluten-free diet and post-gluten challenge treated with placebo or TG2 inhibitor

  Dac EGAC50000000233

• sWGS of plasma and urine cfDNA of RCC patients

  Paired end shallow whole genome sequencing (sWGS) data of cell-free DNA from plasma and urine from RCC patients (DAIMOND cohort)

  Dataset EGAD00001005814

• Fragmentomics analyses of urinary cell-free DNA permit multi-urologic cancer detection and reduction in tissue biopsies for prostate cancer

  This study demonstrated the close association between urinary cell-free DNA (cfDNA) methylation status and the fragmentation patterns in healthy controls and patients with various diseases. Fragmentomics-based methylation analysis (FRAGMA) enables accurate estimation of methylation levels in urinary cfDNA, which is proved by paired bisulfite sequencing and non-bisulfite sequencing data. FRAGMA showed high accuracy in deducing tissue-of-origin of urinary cfDNA in transplantation patients and pregnant women. Moreover, FRAGMA showed great potential in the detection and classification of multiple cancers from the urinary system, including bladder, kidney, and prostate cancer. This study demonstrated that FRAGMA could be applied to improve current diagnostic strategies based on urine samples.

  Study EGAS50000001431

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

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

  Study EGAS00001008051

• Investigating Genetics of Human Natural Short Sleepers (IGHNSS)

  Sleep is essential for life. A good night's sleep is pleasurable and sleep deprivation is stressful. Prolonged sleep loss impairs temperature control, metabolism, immunity, and ultimately leads to death. Extensive observational and epidemiological evidence indicates that optimal sleep duration of 8 hours is associated with the maintenance of good health. In our society, however, most people only get 6.5 - 7 hours. Suboptimal sleep duration has a strong association with mortality and morbidity. Lack of sleep has been linked to cardiovascular diseases, obesity, hypertension, type 2 diabetes, and other health/cognition conditions. It is clear that the biological need for sleep varies dramatically among humans. Sleep and circadian disorders can include Familial Advanced Sleep Phase (FASP), Delayed Sleep Phase (DSP), Advanced Sleep Phase (ASP), Natural Short Sleepers (NSS) or Long Sleeping. In example, Natural Short Sleepers (NSS) have a lifelong tendency to sleep only 4 - 6 hours per night and to awaken refreshed and energetic. Natural Long Sleepers biologically require 9 - 10 hours/night to feel well rested. The 'Sleep and Circadian Disorders Study' (SACDS) at the University of California San Francisco, set out to investigate the mechanisms involved in regulating sleep duration, patterns and sleep quality regulation by identifying and characterization of individuals and families with unusual sleep and circadian rhythm behavior patterns. SACDS participants were screened with a "General Sleep Questionnaire" that inquired about multiple aspects of sleep, including habitual work-day versus non-work day sleep-wake schedules, permits calculation of subjective habitual initial sleep onset, final sleep offset, and number of awakenings. There was an additional screening process including demographic data, sleep, mood, behavioral and general medical questionnaires, plus the study consent. After the extensive screening of 117 participants, blood samples were collected from 38 individuals and of those 10 samples were chosen for whole exome sequencing analysis.

  Study phs001270

• Metadata Public API

  Metadata Rest Endpoints Common Aspects Functionality Identifiers Requests and Responses Request Response Querying Querying by Object Cross-Querying by Object Common Aspects Functionality The Metadata REST API allows EGA users to request metadata from the EGA. Using this api you will be able to obtain the publicly available information from EGA study, sample, experiment, run, analysis, policy, dac and dataset. The API also allows for objects to be cross-referenced in order to obtain for example all the datasets linked to a dac. Identifiers EGA objects can be identified by their unique accession. These are ID's displayed everywhere, shared among all EGA locations and specific for each data type (More information on the list below) EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID Server Request and Response Request All the endpoints implement these two HTTP methods, GET and HEAD. Moreover, there is an authentication layer that allows to disclose the private information about each object if the user runs the endpoint with their token and has permissions to the related dataset. HTTP Method Description GET Returns the objects and their public information (including private information if the user has permissions) HEAD Returns the count of objects to be returned Response API responses are diverse but they always return a status call. Below you have a summary on what these codes mean and some tips that can help you troubleshooting them: HTTP Status Code Description Resolution 200 OK No error handling necessary 206 Partial Content Expected status code when paginating the results. No error handling necessary 400 BAD REQUEST Request incorrectly formulated 401 UNAUTHORISED/FORBIDDEN You do not have permissions over the object you are trying to access. / The authorised user is not permitted to make the given request. 404 NOT FOUND The object/resource you are trying to access does not exist. 500 INTERNAL SERVER ERROR This is a server-side error, try later. If the issue persists, contact the Heldpesk. Querying Querying by Object In the below documentation, worked examples can be found on how to use the API, to query about each unique EGA object. https://metadata.ega-archive.org/analyses/{id} https://metadata.ega-archive.org/dacs/{id} https://metadata.ega-archive.org/datasets/{id} https://metadata.ega-archive.org/runs/{id} https://metadata.ega-archive.org/samples/{id} https://metadata.ega-archive.org/studies/{id} Worked example for the EGA data access committee(DAC) EGAC00001000514 https://metadata.ega-archive.org/dacs/EGAC00001000514 Points to notice Please, be advised that all EGA objects can be queried by using the same endpoint. For example: https://metadata.ega-archive.org/datasets Returns all the datasets registered at the EGA. https://metadata.ega-archive.org/datasets?limit=5&offset=15 Returns 5 results skipping the initial 15 results. Cross-Querying by Object The EGA REST API Metadata also allows for the crossquerying of public metadata. For example, should I want to query the datasets included in the ICGC DAC: https://metadata.ega-archive.org/dacs/EGAC00001000010/datasets Below, you can find worked examples on how to perform the call to the API. https://metadata.ega-archive.org/datasets/EGAD00001000645/analyses https://metadata.ega-archive.org/datasetsEGAD00001000645/files https://metadata.ega-archive.org/datasets/EGAD00001000620/runs https://metadata.ega-archive.org/datasets/EGAD00001000620/samples https://metadata.ega-archive.org/samples/EGAN00001092114/datasets https://metadata.ega-archive.org/files/EGAF00000056146/dacs https://metadata.ega-archive.org/files/EGAF00000056146/datasets https://metadata.ega-archive.org/files/EGAF00000056146/studies There are more endpoints included in this category. Please, find all the possibilities (green tick) in the table below. Table The table displays in a ordered fashion the objects that can be crossreferenced using the metadata API. BY Analysis Dac Dataset Experiment Policy Run Sample Study File Analysis ✔ ✔ Dac ✔ ✔ Dataset ✔ ✔ ✔ ✔ Experiment ✔ ✔ ✔ ✔ Policy ✔ Run ✔ ✔ ✔ Sample ✔ ✔* ✔ Study ✔ ✔ ✔ ✔ ✔ ✔* File ✔ *: These cross queries do not include data from Array-File submissions. Check out the SPEC

  Documentation discovery/metadata/public-metadata-api