Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Transcriptome profiles of B cells from MS patients and healthy controls

ABSTRACT: Transcriptome profiles of B cells from MS patients and healthy controls

PROVIDER: PRJNA727413 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

DNA methylation profiles of four immune cell types from MS patients and healthy controls

Project description:DNA methylation profiles of four immune cell types from MS patients and healthy controls

| PRJNA727170 | ENA

Transcriptome profiles of B cells from MS patients and healthy controls

Project description:How epigenetic changes contribute to MS pathogenesis is still poorly understood. Therefore, we conducted a comprehensive analysis of genome-wide DNA methylation patterns in four immune cell populations isolated from MS patients at clinical disease onset. We also performed parallel transcriptome analysis in B cells to better understand the functional consequences of the DNA methylation changes in MS.

2022-01-18 | GSE173789 | GEO

DNA methylation profiles of four immune cell types from MS patients and healthy controls

2022-01-18 | GSE173787 | GEO

longitudinal expression profiling in whole blood of multiple sclerosis patients and controls [MS vs Ctrl Replication dataset]

2013-06-17 | GSE41849 | GEO

longitudinal expression profiling in whole blood of multiple sclerosis patients and controls [MS vs Ctrl Discovery dataset]

2013-06-17 | GSE41848 | GEO

Serum exosomal miRNA profiles in fulminant myocarditis patients and healthy controls

Project description:Serum exosomal miRNA profiles in fulminant myocarditis patients and healthy controls

| PRJNA615110 | ENA

Single-cell transcriptomic analysis of blood T cells from healthy controls, MS patients and COVID-19 patients by 10X genomics

Project description:In order to better understand the functional properties of this type of cells under different circumstances, we integrated the single-cell RNA-seq data of peripheral blood CD8+ T cells from healthy subjects, MS patients and COVID-19 patients generated from the 10X Genomics platform using the Seurat package. KIR+CD8+ T cells from different conditions (healthy, MS, and COVID-19) formed a distinct cluster with high expression of effector genes (GZMB and PRF1) as well as KIR transcripts. These findings reveal the commonality of KIR+CD8+ T cells across physiological and diseased status as well as their uniqueness relative to other CD8+ T cells.

2022-03-08 | GSE193770 | GEO

Quantitative Analysis of lncRNAs expression profiles between TB patients and healthy controls

Project description:Quantitative Analysis of lncRNAs expression profiles between TB patients and healthy controls

| PRJNA518102 | ENA

longitudinal expression profiling in whole blood of multiple sclerosis patients and controls [MS vs Ctrl Replication dataset]

Project description:Multiple sclerosis is the most common autoimmune disease of the central nervous system. Studying whole blood RNA from a cohort of 195 MS patients and 66 healthy controls, we identified gene expression signatures for interferon treatment and disease status by microarray analysis. Blood was collected at multiple time points (up to 3 for patients, 2 for controls). Patients were either untreated or treated with Interferon. In total, 626 Affymetrix exon arrays were analyzed, split into discovery and replication data sets. This metadata file contains information on all samples processed in the replication data set (n=102) when we compared gene expression in untreated MS patients (n=27) to healthy controls (n=25). The following comparisons were made: untreated MS vs Controls (discovery and replication), untreated vs Interferon treated MS (discovery and replication). For each comparison, respective arrays were processed (background corrected and normalized) together, but seperate from other comparisons. The two time points for controls were averaged. For the first comparison, we report differentially expressed genes at an FDR cutoff of 0.1 at any of the three tested time points in MS patients in the discovery data set. For the second comparison, the FDR cutoff was 0.001. The respective genes were validated in the replication data set when they passed a nominal p-value cutoff of 0.05 at any of the three tested time points.

2013-06-17 | E-GEOD-41849 | biostudies-arrayexpress

longitudinal expression profiling in whole blood of multiple sclerosis patients and controls [MS vs Ctrl Discovery dataset]

Project description:Multiple sclerosis is the most common autoimmune disease of the central nervous system. Studying whole blood RNA from a cohort of 195 MS patients and 66 healthy controls, we identified gene expression signatures for interferon treatment and disease status by microarray analysis. Blood was collected at multiple time points (up to 3 for patients, 2 for controls). Patients were either untreated or treated with Interferon. In total, 626 Affymetrix exon arrays were analyzed, split into discovery and replication data sets. This metadata file contains information on all samples processed in the discovery data set (n=212) when we compared gene expression in untreated MS patients (n=62) to healthy controls (n=41). The following comparisons were made: untreated MS vs Controls (discovery and replication), untreated vs Interferon treated MS (discovery and replication). For each comparison, respective arrays were processed (background corrected and normalized) together, but seperate from other comparisons. The two time points for controls were averaged. For the first comparison, we report differentially expressed genes at an FDR cutoff of 0.1 at any of the three tested time points in MS patients in the discovery data set. For the second comparison, the FDR cutoff was 0.001. The respective genes were validated in the replication data set when they passed a nominal p-value cutoff of 0.05 at any of the three tested time points.

2013-06-17 | E-GEOD-41848 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data