Project description:In order to study the gene expression profiles of monocyte and macrophages, we collected three type of cells and performed pair-wised comparison. It includes human peripheral blood monocyte (MONO), human peripheral blood monocyte derived macrophages treated with M-CSF (MACRO)and primary alveolar macrophages (BAL). All the experiments are performed comparing two of the three cell types from the same person (total 4 persons). Totally we got three set of microarray data, MONO/MACRO, MONO/BAL and MACRO/BAL with 4 biological replicates.

2006-12-01 | E-MEXP-524 | biostudies-arrayexpress

scCRISPR-screen in human monocyte derived macropahges

Project description:To determine whether the hits derived from a genome-wide murine BMDM screen regulated human macrophage phenorypes, we established a framework that coupled genetic perturbation with phenotypic analysis at single-cell resolution in primary human monocyte-derived macrophages (MDM scCRISPR-seq).

2024-07-18 | GSE210950 | GEO

Deoxynivalenol affects the gene expression of A549 lung epithelial cells

Project description:Deoxynivalenol (DON) is an important Fusarium toxin of concern for food safety. The inhalation of powder contaminated with deoxynivalenol is possible and may cause lung toxicity. In this study, we investigated the gene expression profile of A549 cells treated with 0.2 microg/mL deoxynivalenol by microarray analysis. In total, 16 genes and 5 noncoding RNAs were significantly affected by deoxynivalenol treatment.

2016-02-29 | GSE60928 | GEO

Human monocyte derived macrophage microarray analysis

Project description:Microarray data was acquired from human primary monocyte-derived macrophages in order to test the validity of a graphical software package (z-score outlier detection (ZODET)) Complex human diseases can show significant heterogeneity between patients with the same phenotypic disorder. An outlier detection strategy was developed to identify variants at the level of gene transcription that are of potential biological and phenotypic importance. Here we describe a graphical software package (z-score outlier detection (ZODET)) that enables identification and visualisation of gross abnormalities in gene expression (outliers) in individuals, using whole genome microarray data. Mean and standard deviation of expression in a healthy control cohort is used to detect both over and under-expressed probes in individual test subjects. We compared the potential of ZODET to detect outlier genes in gene expression datasets with a previously described statistical method, gene tissue index (GTI), using a simulated expression dataset and a publicly available monocyte-derived macrophage microarray dataset. Taken together, these results support ZODET as a novel approach to identify outlier genes of potential pathogenic relevance in complex human diseases. The algorithm is implemented using R packages and java. 40 volunteer were bled and primary monocyte derived macrophages were cultured. These samples were then randomised into two equal sized groups (control - A1-20 and experimental - B1-20) and run on the ZODET software.

2014-11-05 | E-GEOD-51256 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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