Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: 2019 fungi test

PROVIDER: PRJNA827190 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR18774435_1.fastq.gz	Fastqsanger.gz
	SRR18774435_2.fastq.gz	Fastqsanger.gz
	SRR18774436_1.fastq.gz	Fastqsanger.gz
	SRR18774436_2.fastq.gz	Fastqsanger.gz
	SRR18774437_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 48

Similar Datasets

Project description:2019 fungi diversity test

| PRJNA827242 | ENA

Project description:2019 test data

| PRJNA827187 | ENA

Project description:2019 bacterial diversity test

| PRJNA827236 | ENA

Project description:2019 GenomeTrakr/PulseNet Proficiency Test Exercise

| PRJNA681235 | ENA

Project description:2020 fungi test data

| PRJNA827232 | ENA

Evaluation of transcriptomic profiles of peripheral blood myeloid cell subsets of RA patients in remission prior to cDMARD withdrawal, and at the point of flare / 6 months after in sustained remission

Project description:To test the contribution of distinct ST-DC populations to either autoimmunity and inflammation or sustained disease remission, we evaluated the phenotypes of their blood precursors in a human model of disease flare following treatment withdrawal in RA patients in disease remission (the BioRRA study, (Baker et al., 2019)). We investigated the frequency and phenotype of PB DC2 and PB-DC3 of RA patients (n=12) in sustained clinical and ultrasound remission achieved with cDMARDs (Baker et al., 2019) by carrying out, and analysing single cell sequencing data at baseline remission levels, and upon endpoint after treatment withdrawal. We identified that PB DCs differ transcriptionally, but not proportionally, at the baseline of patients who sustain remission, versus those who go on to flare, and at endpoint. We propose that the transcriptomic profile of these peripheral blood DCs could be used as a biomarker of flare in remission RA patients.

2024-12-09 | E-MTAB-14169 | biostudies-arrayexpress

Early Predicting COVID-19 Severity Value with Extracellular Vesicles and Extracellular RNAs

Project description:The SARS-CoV-2 outbreak started on December 2019 in China and rapidly spread worldwide. Clinical manifestations of Coronavirus-disease 2019 (COVID-19) vary broadly, ranging from asymptomatic infection to acute respiratory failure and death, yet the underlying mechanisms and predictive biomarkers for this high variability are still unknown. Emerging evidence has shown that circulating extracellular vesicles (EVs) and extracellular RNAs (exRNAs) are functionally involved in a number of physiologic and pathologic processes. To test the hypothesis that these extracellular components are a key determinant of severity in COVID-19, we collected 31 serum samples from mild COVID-19 patients at admission in single center. After standard therapy without corticosteroids, 9 of 31 patients became severe COVID-19. We analyzed exRNA profiles from the 31 serums and 10 healthy controls for predicting COVID-19 severity value.

2022-03-31 | GSE158877 | GEO

Development and application of key technologies of a novel early warning system for colorectal cancer basing on microbial characteristics

Project description:Interventions: Gold Standard:pathological examination;Index test:new colorectal cancer screening kit Primary outcome(s): Intestinal bacteria;Intestinal fungi;Intestinal virus Study Design: Sequential

| 2726246 | ecrin-mdr-crc

Identifying crossover locations in Arabidopsis thaliana asy1/+ Col × Ler F2 populations using genotyping-by-sequencing

Project description:Genomic DNA from 191 asy1/+ Col x Ler F2 individuals was extracted using CTAB and used to generate sequencing libraries as described (Lawrence et al, 2019 Current Biology). Sequencing data was analysed to identify crossovers using the TIGER pipeline as previously described (Rowan et al, 2015 G3 (Bethesda); Yelina et al, 2015 Genes & Dev; Lawrence et al, 2019 Current Biology).

2020-05-18 | E-MTAB-8725 | biostudies-arrayexpress

Severe acute respiratory syndrome coronavirus 2

Project description:A Clinical test of 2019-nCoV Nucleic acid detection kit and downstream software

| PRJNA1058688 | ENA