Ontology highlight
ABSTRACT:
PROVIDER: PRJNA636773 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11908224_1.fastq.gz | Fastqsanger.gz | |||
| SRR11908224_2.fastq.gz | Fastqsanger.gz | |||
| SRR11908225_1.fastq.gz | Fastqsanger.gz | |||
| SRR11908225_2.fastq.gz | Fastqsanger.gz | |||
| SRR11908226_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 12 |
Similar Datasets
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9189 | biostudies-arrayexpress
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9191 | biostudies-arrayexpress
Project description:Copy number alterations (CNAs) play a fundamental role in cancer development and constitute a potential tool for tailored treatments. The CNAs recognition in formalin fixed paraffin embedded (FFPE) material, to date, relies on fluorescence in situ hybridization, but the introduction of large-scale next-generation sequencing (NGS) has dramatically improved their discovery at genome-wide level. The detection of CNAs by NGS in FFPE material is, nonetheless, a complex issue, which still requires validation studies. Herein, the CNAs detection by a widely used NGS assay (Oncomine Comprehensive Assay plus®, OCA+) were evaluated in 14 FFPE samples mirroring diagnostic daily practice and compared to a whole-genome assay. OCA+, a targeted DNA panel, showed lower CNAs detection sensitivity and equal specificity for gains and losses. According to proprietary software pipeline, OCA+ accurately identify gains characterized by CN ≥5,2. A much less robust threshold (CN ≤1.18) was identified that maximized the difference between true and false positive losses. Orthogonal FISH tests validated seven CNAs characterized by CN gain ≥6 or complete loss. Considering the CNAs growing significance in precision medicine, our findings further prompt towards a robust validation of NGS detection in FFPE materials.
2025-02-12 | GSE277695 | GEO
Project description:The plasma levels of tissue-specific microRNAs can be used as prognostic and diagnostic biomarkers for chronic and acute diseases. Thereby, the combination of diverse miRNAs into biomarker signatures using multivariate statistics seems especially powerful in view to tissue and condition specific miRNA shedding into the plasma. Although Next-Generation Sequencing (NGS) technology enables to analyse circulating microRNAs on a genome-scale level, it suffers from potential biases (e.g. adapter ligation bias) and lacks absolute transcript quantitation. In order to develop a robust NGS discovery assay for genome-scale quantitation of circulating microRNAs we first evaluated the sensitivity, repeatability and ligation bias of four commercially available small RNA library preparation protocols. The protocol from RealSeq Biosciences was selected based on its performance and usability, and coupled with a novel panel of exogenous small RNA spike-in controls to enable absolute quantitation and ensure comparability of data across independent NGS experiments. The established MicroRNA Next-Generation-Sequencing Discovery Assay (miND) was validated for its relative accuracy, precision, analytical measurement range and sequencing bias and was considered fit-for-purpose for microRNA biomarker discovery. Summarized, all these criteria were met and thus our analytical platform is considered fit-for-purpose for microRNA biomarker discovery from plasma, serum, cerebrospinal fluid (CSF), synovial fluid (SF), or extracellular vesicles (EV) extracted from cell culture medium in the setting of any diagnostic, prognostic or patient stratification need.
2022-01-20 | GSE189930 | GEO
Project description:Subgroup J avian leukemia is a type of oncology infectious disease caused by Subtype J of avian leukosis virus (ALV-J). It mainly encroaches on bone marrow cells, and metastasizes to liver, kidney, splenic ellipsoids and other organs, leading to myeloid leukosis (ML) and other malignancies, resulting in significant economic losses. microRNA play important roles in oncology infectious diseases. We used miRNA microarray analysis to detail the relationship of aberrant microRNAs and chicken ALV-J leukemia, and to try to find the potential diagnostic and therapeutic target for infections of subtype J of leukemia. ALV-J-infected and non-infected ten-week-old chicken liver tissues were sampled for the array assay. A1, A2, and A3 are the ALV-J infection group samples, and DA1, DA2, and DA3 are the control samples. 623 mature miRNA sequences were assembled and integrated into the LC miRNA microarray design, and different miRNA expressions were measured on the 7000HT Fast Real-Time PCR system.
2014-03-10 | E-GEOD-28434 | biostudies-arrayexpress
Project description:Comparing molecular signatures of psoriasis and eczema in patients co-affected by both diseases provides a comprehensive understanding of disease pathogenesis as well as a diagnostic tool to differentiate these widespread inflammatory skin diseases.
2014-05-01 | GSE57225 | GEO
Project description:RNA sequencing data were generated from the whole blood of children with a range of acute febrile illnesses. These data were used as the validation cohort for a multiclass diagnostic gene expression signature for the discrimination of 18 infectious and inflammatory diseases which was discovered using publicly available microarray datasets.
2022-11-22 | E-MTAB-11671 | biostudies-arrayexpress