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• International Age-Related Macular Degeneration Genomics Consortium - Exome Chip Experiment

  Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. To further our understanding of AMD genetics, we examined the contribution of common and rare genetic variation in the International AMD Genomics Consortium that included ~50,000 samples of 26 AMD case - control cohorts that were jointly genotyped. Analyzing 16,144 patients with late stage AMD and 17,832 controls, we identified 52 independently associated common and rare variants distributed across 34 loci. Besides these single variant signals, we also observed gene-based enrichment of very rare coding variants (frequency < 0.1%) in cases that implicated causal roles for CFH, CFI and TIMP3 in three of the known AMD risk loci. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.

  Study phs001039

• QUANTitative Chest Computed Tomography UnMasking Emphysema Progression in Alpha-1 Antitrypsin Deficiency

  AAT deficiency is a genetic disorder associated with emphysema. Spirometry, the lung function test that measures how well the lungs exhale air, is used to diagnose and track the progression of emphysema. Some studies have suggested that forced expiratory volume in 1 second (FEV1) measurements, a type of spirometry test, may lack accuracy in detecting disease progression in cases of severe AAT deficiency. Another method, high resolution chest CT scans, may be more accurate at measuring the progression of emphysema. The purpose of this study is to determine if high resolution CT scans are better at detecting the progression of emphysema than lung function tests. Results from this study may lead to the development of a more accurate way to assess lung tissue loss and may improve the understanding of lung destruction in AAT deficiency. This study will last 4 years and will enroll people with AAT deficiency who have nearly normal lung function test results. Study visits, each lasting about 4 hours, will occur at baseline and months 6, 12, 18, 24, and 36. At each visit, participants will undergo lung function tests, a CT scan, blood collection, and a physical exam. Female participants will have urine collected for a pregnancy test. All participants will also complete questionnaires to assess health status and lung function. Study researchers will call participants every 2 months to collect information on lung disease symptoms and medication changes.

  Study phs000698

• M116 scRNA-seq

  scRNA-seq was performed using Chromium Next GEM Single Cell 3’ Kit v3.1 (10X Genomics) according to the manufacturer’s instructions. Briefly, M116's PBMCs were thawed and quantified in order to calculate the number of cells to be loaded. Then, barcoded Single Cell 3ʹ Gel Beads, a master mix containing PBMCs, and Partitioning Oil were combined onto the Chromium Next GEM Chip G to generate Gel Beads-In-Emulsion (GEMs), where polyadenylated mRNAs were reverse transcribed. This way, all generated cDNAs from the same cell shared a common 10X Barcode. Following the reverse transcription, GEMs were broken and cDNAs were amplified and cleaned up with SPRIselect beads (Beckman Coulter®). Next, a portion of these cDNAs were enzymatically fragmented and subjected to adaptor ligation before using them as a PCR template for the incorporation of i5/i7 indexes. Finally, libraries were purified with SPRIselect beads, quantified and quality checked by using the 2200 TapeStation (Agilent®), and subjected to paired-end 150-bp sequencing (Novaseq systems, Illumina®) following standard practices at external facilities (Novogene®). Files types included in this dataset are raw Fastq files.

  Dataset EGAD50000001289

• Genetic mechanisms of resistance to chemotherapy in breast cancer

  Resistance towards chemotherapy is one of the main causes of treatment failure and deathamong breast cancer patients.The main objective of this project is toidentify genetic mechanisms causing some breast cancer patients not torespond to a particluar type of chemotherapy (epirubicin) while otherpatients respond very well to the same treatment. In the project wewill perform genome / exome sequencing of a selection of breast cancerpatients (n=30). These patients are drawn from a cohort where allpatients have recieved treatment with epirubicin monotherapy before surgical removal of alocally advanced breast tumour, and where all patients have beensubjected to objective evaluation of the response to thetherapy. Subsequent to sequencing, we will analyse the data andcompare with the clinical data for each patient (object response totherapy). The main aim being to identify mutations that are associatedwith resistance to epirubicin. Identification of mutations with strongpredictive value, may have a direct impact on cancer treatment sinceit opens the possibility for genetic testing of a tumour, and desicionon which drug is likely to work best, prior to treatment start.

  Dataset EGAD00001000264

• 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

• Peripheral blood DNA transcriptomics of vedolizumab treatment response in patients with Crohn's disease

  Data pertains longitudinal transcriptomic data measured from blood obtained from patients with Crohn's disease that were starting treatment with vedolizumab. Samples were obtained prior to treatment and approximately 26 weeks into treatment during response assessment. At response assessment, patients were classified as responders (R) or non-responders (NR) based on a strict combination of endoscopic, biochemical and clinical criteria: ≥50% reduction in the endoscopic SES-CD score, corticosteroid-free clinical remission (≥3 point drop98 in HBI or HBI ≤4 and no systemic steroids) and/or biochemical response (C-reactive protein (CRP) and fecal calprotectin reduction ≥50% or ≤5 mg/L and fecal calprotectin ≤250 µg/g). Modified response was defined as a combination of corticosteroid-free clinical- (HBI ≤4) and biochemical (CRP ≤5 mg/L and/or fecal calprotectin ≤250 µg/g) remission between week 26-52 without treatment change through week 52. Transcriptomic analyses was conducted through RNA sequencing, wherein mRNA was extracted utilizing the QIAsymphony system, converted into cDNA and sequenced in a paired-end format on the Illumina NovaSeq6000 at the Amsterdam UMC Core Facility Genomics, generating a dataset comprising 40 million 150 bp-reads.

  Dataset EGAD50000000385

• Peripheral blood DNA transcriptomics of ustekinumab treatment response in patients with Crohn's disease

  Data pertains longitudinal transcriptomic data measured from blood obtained from patients with Crohn's disease that were starting treatment with ustekinumab. Samples were obtained prior to treatment and approximately 26 weeks into treatment during response assessment. At response assessment, patients were classified as responders (R) or non-responders (NR) based on a strict combination of endoscopic, biochemical and clinical criteria: ≥50% reduction in the endoscopic SES-CD score, corticosteroid-free clinical remission (≥3 point drop98 in HBI or HBI ≤4 and no systemic steroids) and/or biochemical response (C-reactive protein (CRP) and fecal calprotectin reduction ≥50% or ≤5 mg/L and fecal calprotectin ≤250 µg/g). Modified response was defined as a combination of corticosteroid-free clinical- (HBI ≤4) and biochemical (CRP ≤5 mg/L and/or fecal calprotectin ≤250 µg/g) remission between week 26-52 without treatment change through week 52. Transcriptomic analyses was conducted through RNA sequencing, wherein mRNA was extracted utilizing the QIAsymphony system, converted into cDNA and sequenced in a paired-end format on the Illumina NovaSeq6000 at the Amsterdam UMC Core Facility Genomics, generating a dataset comprising 40 million 150 bp-reads.

  Dataset EGAD50000000386

• Reconstituting the transcriptome and DNA methylome landscapes of human implantation at single-cell resolution

  Implantation is a milestone event during mammalian embryogenesis. Due to the extreme difficulty of obtaining in vivo human early post-implantation embryos, the gene regulatory network and epigenetics controlling human embryo implantation remains elusive. Here, combining an in vitro culture system for human post-implantation development and single-cell omics sequencing technologies, over 10,000 single cells at five representative stages of pre/post-implantation development were systematically analyzed. Unsupervised dimensionality reduction and clustering algorithm of the transcriptome data show stepwise implantation routes for the epiblast, primitive endoderm, and trophectoderm lineages, suggesting preparation for the establishment of a mother-to-offspring connection after implantation. Female embryos showed asynchronous progress of dosage loss of X chromosomes during implantation. Furthermore, using the single cell trio-Seq (scTrio-Seq) strategy, re-methylation of the genomes of all the three lineages was unambiguously revealed. Surprisingly, the genome re-methylation of PE lineage were much slower than both EPI and TE lineages during the implantation process, indicating distinct methylome features between EPI and PE although both of which were derived from ICM. Collectively, our work paves the way for understanding the complex molecular mechanisms that regulate human embryo implantation, informing new insights and future efforts in early embryonic development and reproductive medicine.

  Study EGAS00001003443

• Feasibility and safety of a multi-cancer blood test for screening and intervention

  We evaluated the feasibility and safety of blood testing for cancer in an interventional study of 10,006 women. Positive tests for DNA or protein were independently confirmed and diagnostic PET-CT imaging was used to localize disease. During the study, 26 cancers were first detected by blood testing, 24 more by standard-of-care screening, and 46 by neither approach. Surgicalexcision of the primary tumors was performed on 12 cancers first detected by blood testing.1.0% of participants underwent PET-CT imaging based on false positive blood tests, and 0.22% underwent a futile invasive diagnostic procedure. These data demonstrate that multi-cancer blood testing, when followed by PET-CT localization, can be safely incorporated into routineclinical care, in some cases leading to surgery with intent to cure. Further studies will be required to determine the clinical validity and utility of multi-cancer blood testing.

  Study EGAS00001004372

• All counts

  This dataset is the expression profiling by high throughput sequencing, including all counts of genes for all samples in two groups. It includes 26 samples totally (Lean healthy group includes 12 samples: s001/SR01_Bright, s002/SR01_Dim, s004/SR02_Bright, s005/SR04_Dim, s006/SR04_Bright, s007/SR05_Dim, s008/SR05_Bright, s009/SR06_Bright, s011/SR07_Dim, s012/SR07_Bright, s013/SR08_Bright, s014/SR08_Dim; DM2 group includes 14 samples: s015/SR201_Bright, s017/SR202_Bright, s018/SR202_Dim, s019/SR203_Bright, s020/SR203_Dim, s021/SR204_Bright, s022/SR204_Dim, s023/SR205_Dim, s025/SR206_Dim, s026/SR206_Bright, s027/SR207_Dim, s028/SR207_Bright, s029/SR208_Bright, s030/SR208_Dim). It is a TAB file.

  Dataset EGAD50000001715