Clinical metagenome
Ontology highlight
ABSTRACT:
PROVIDER: PRJDB10711 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| DRR252161_1.fastq.gz | Fastqsanger.gz | |||
| DRR252161_2.fastq.gz | Fastqsanger.gz | |||
| DRR252162_1.fastq.gz | Fastqsanger.gz | |||
| DRR252162_2.fastq.gz | Fastqsanger.gz | |||
| DRR252163_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 10 |
Similar Datasets
Project description:Metagenomics for pathogens detection from pediatric patients with meningitis
| PRJDB12113 | ENA
Project description:Targeted metagenomics for clinical detection and discovery of bacterial tickborne pathogens
| PRJNA637310 | ENA
Project description:Detection of food borne pathogens via Metagenomics approach
| PRJEB27356 | ENA
Project description:PFAPA, the syndrome of periodic fever associated with aphthous stomatitis, pharyngitis and/or cervical adenitis, is the most common periodic fever disease in children. Cases are mostly sporadic; the etiopathogenesis is unknown. In order to shed more insights into pathogenesis, we performed microarray expression analysis on samples from patients with PFAPA during and between flares, healthy controls and patients with hereditary autoinflammatory diseases during flares. RNA was extracted from whole peripheral blood from six patients with PFAPA syndrome during flares and asymptomatic intervals, six healthy controls and six patients with hereditary autoinflammatory diseases (2 familial Mediterranean fever (FMF), 1 TNF-receptor-asociated periodic fever syndrome (TRAPS) and 3 cryopyrin-associated periodic syndromes (CAPS)).
2011-06-20 | E-GEOD-17732 | biostudies-arrayexpress
Project description:This project contains raw data, intermediate files and results is a re-analysis of the publicly available dataset from the PRIDE dataset PXD005780. The RAW files were processed using ThermoRawFileParser, SearchGUI and PeptideShaker through standard settings (see ‘Data Processing Protocol’). This reanalysis work is part of the MetaPUF (MetaProteomics with Unknown Function) project, which is a collaboration between EMBL-EBI and the University of Luxembourg. The dataset was selected with the following conditions: 1. It has been made publicly available in PRIDE and focuses on metaproteomics of the human gut; 2. The corresponding metagenomics assemblies were also available from ENA (European Nucleotide Archive) or MGnify. The processed peptide reports for each sample are available to view at the contig level on the MGnify website. In total, the reanalysis identified 15,417 unique proteins from 15 samples.
2022-05-04 | PXD032303 | Pride
Project description:PFAPA, the syndrome of periodic fever associated with aphthous stomatitis, pharyngitis and/or cervical adenitis, is the most common periodic fever disease in children. Cases are mostly sporadic; the etiopathogenesis is unknown. In order to shed more insights into pathogenesis, we performed microarray expression analysis on samples from patients with PFAPA during and between flares, healthy controls and patients with hereditary autoinflammatory diseases during flares.
2011-06-20 | GSE17732 | GEO
Project description:Comparison of methods for blood pathogens detection
| PRJNA693402 | ENA
Project description:A common technique used for sensitive and specific diagnostic virus detection in clinical samples is PCR. However, an unbiased diagnostic microarray containing probes for all human pathogens could replace hundreds of individual PCR-reactions and remove the need for a clear clinical hypothesis regarding a suspected pathogen. We have established such a diagnostic platform for unbiased random amplification and subsequent microarray identification of viral pathogens in clinical samples. We show that Phi29 polymerase-amplification of a diverse set of clinical samples generates enough viral material for successful identification by the Microbial Detection Array developed at the Lawrence Livermore National Laboratory, California, USA, demonstrating the potential of the microarray technique for broad-spectrum pathogen detection. We conclude that this method detects both DNA and RNA virus, present in the same sample, as well as differentiates between different virus subtypes. We propose this assay for unbiased diagnostic analysis of all viruses in clinical samples.
2011-04-14 | GSE28597 | GEO
Project description:Carcinomas of unknown primary origin constitute 3-5% of all newly diagnosed metastatic cancers, of which the primary source is difficult to classify with current histological methods. Effective cancer treatment depends on early and accurate identification of the tumor, which is why patients with metastases of unknown origin have poor prognosis and short survival. Because microRNA expression is highly tissue specific, the microRNA profile of a metastasis may be used to identify its origin. As a first step to realize this goal, we evaluated the potential of microRNA profiling for identification of the primary tumor of known metastases. 208 formalin-fixed paraffin-embedded samples representing 15 different histologies were profiled on an LNA-enhanced microarray platform, which allows for highly sensitive and specific detection of microRNA. Based on these data, we developed and cross-validated a novel classification algorithm, LASSO (Least Absolute Shrinkage and Selection Operator), which had an overall accuracy of 85%. When the classifier was applied on an independent test set of 48 metastases, the primary site was correctly identified in 42 cases (88% accuracy). Our findings suggest that microRNA expression profiling on paraffin tissue can efficiently predict the primary origin of a tumor, and may provide pathologists with a molecular diagnostic tool that can improve their capability to correctly identify the origin of hitherto unidentifiable metastatic tumors, and eventually, enable tailored therapy.
2013-12-01 | GSE50890 | GEO