27 results for ""45+references"+"protein+family"+"pdf""

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• ML modeling data & code

  Rmarkdown code, PDF, and Rdata file to recapitulate the paper's primary figures and machine learning model development.

  Dataset EGAD00001009764

• Greek

  Greek Multiple Sclerosis cases and controls

  Dataset EGAD00010002115

• US

  US Multiple Sclerosis cases and controls

  Dataset EGAD00010002116

• Australia

  Australia Multiple Sclerosis cases and controls

  Dataset EGAD00010002117

• Finland-Immuno

  Finland Multiple Sclerosis case

  Dataset EGAD00010002048

• USA-Immuno

  USA Multiple Sclerosis cases and controls

  Dataset EGAD00010002043

• SAHGP Dataset

  HumanOmni25M-8v1-1

  Dataset EGAD00010001418

• Belgium-Immuno

  Belgium Multiple Sclerosis cases and normal controls

  Dataset EGAD00010002045

• France-Immuno

  France Multiple Sclerosis cases and normal controls

  Dataset EGAD00010002046

• AUSNZ-Immuno

  Australia and New Zealand Multiple Sclerosis case

  Dataset EGAD00010002047

• Germany-Immuno

  Germany Multiple Sclerosis cases and normal controls

  Dataset EGAD00010002044

• R code

  R code to run analyses on anonymized data from ABACUS for IMvigor010 ctDNA publication.

  Dataset EGAD00001007652

• EGAD00010000250

  NBS control samples

  Dataset EGAD00010000250

• EGAD00010000246

  Coeliac disease cases and control samples. (1958BC samples excluded)

  Dataset EGAD00010000246

• EGAD00010000248

  1958BC control samples

  Dataset EGAD00010000248

• R code

  R code to run analyses on anonymized data from IMvigor010 ctDNA publication.

  Dataset EGAD00001007654

• Capture Hi-C on Hodgkin lymphoma cell line L-428

  In situ promoter capture Hi-C on Hodgkin lymphoma cell line L-428 in experimental triplicates. Hi-C libraries were prepared as previously described (Orlando et al., 2018, https://currentprotocols.onlinelibrary.wiley.com/doi/pdf/10.1002/cphg.63). Promoter capture was based on 32,313 biotinylated 120-mer RNA baits (Agilent). Hi-C libraries were sequenced using Illumina HiSeq 2000 technology. The files are in FASTQ format.

  Study EGAS00001003032

• Mexican_Biobank_Genotypes

  Samples from the Mexican Biobank

  Dataset EGAD00010002361

• UK_ReplicationChip

  This dataset includes data from UK Multiple Sclerosis (MS) cases that were recruited through the University of Cambridge and included in the IMSGC Replicationchip experiment. Data from UK controls and additional UK cases that were recruited through other UK centres is available by direct application to those respective centres, as described in the original paper.

  Dataset EGAD00010002118

• Capture Hi-C on Hodgkin lymphoma

  In situ promoter capture Hi-C on Hodgkin lymphoma cell line L-428 in experimental triplicates. Hi-C libraries were prepared as previously described (Orlando et al., 2018, https://currentprotocols.onlinelibrary.wiley.com/doi/pdf/10.1002/cphg.63). Promoter capture was based on 32,313 biotinylated 120-mer RNA baits (Agilent). Hi-C libraries were sequenced using Illumina HiSeq 2000 technology. The files are in FASTQ format.

  Dataset EGAD00001004321

• AWI-GEN 2 Microbiome Dataset

  AWI-Gen Phase 2 Microbiome Project for 1820 samples.

  Dataset EGAD00001015449

• AWI-GEN 2 Phenotype Dataset

  Core phentoype data for AWI-Gen Phase 2 Microbiome Project for 1824 samples.

  Dataset EGAD00001015440

• Serum proteomics of aortic diseases

  Aortic diseases are a rare but potentially life-threatening condition. We present a serum proteomic study for a spectrum of aortic diseases including thoracic aortic aneurysms (n = 11), chronic dissections (n = 9), acute aortic dissections (n = 11), and surgically treated dissections (n = 19) as well as healthy controls (n = 10) and patients of coronary heart disease (n = 10) to represent non-aortic cardiovascular disease. In total, we identified and quantified 425 proteins across all 70 samples. The different aortic diseases represented distinguishable proteome profiles. We identified protein clusters that positively or negatively correlate with disease severity, including increase of cytosolic tissue leakage proteins and decrease of components of the coagulation and complement system. Further, we identified a serum proteome fingerprint of acute aortic dissections, consisting, among others, of enriched inflammatory markers such as C-reactive protein and members of the S100 protein family. The study underlines the applicability of serum proteomics for the investigation of aortic diseases and highlights the possibility to establish disease-specific prognostic markers.

  Study EGAS00001006201

• H3Africa AWI-GEN Phase 1 Phenotype

  The phenotypic data for ~12500 samples of the AWI-Gen Phase 1 Population cross-sectional study of older adults (mostly between 40 and 60 years), men and women. Six study sites in four sub-Saharan African counties including Ghana, Burkina Faso, Kenya and South Africa. Some groups are missing data for specific variables. Data includes questionnaire data (demography, health history, family health history, behaviour and infection data); anthropometry; and laboratory assays on blood and urine.

  Dataset EGAD00001006425

• Rare Disease Synthetic Dataset

  The purpose of this project is to provide public human datasets for the study of rare diseases. The use of public human genomic background combined with the in-silico insertion of real disease-causing variants enable to have a representative dataset for testing purposes without facing ethical and legal issues associated with the use of human sensitive data. This project aims to help development of technical implementations for rare disease data integration, analysis, discovery, and federated access.

  Dataset EGAD00001008392

• DDD DATAFREEZE 2013-12-18: 1133 trios - VCF files (Ref: DDD Nature 2015)

  DDD DATAFREEZE 2013-12-18: 1133 trios - VCF files (Ref: DDD Nature 2015)

  Dataset EGAD00001001355

• DDD DATAFREEZE 2013-12-18: 1133 trios - README, family trios, phenotypes, validated DNMs (Ref: DDD Nature 2015)

  DDD DATAFREEZE 2013-12-18: 1133 trios - README, family trios, phenotypes, validated DNMs (Ref: DDD Nature 2015)

  Dataset EGAD00001001413