GEO DataSets

(Submitter supplied) In the lungs of chronic obstructive pulmonary disease (COPD) patients, numerous cell types interact in a structurally abnormal and inflammatory microenvironment. Assessing gene expression in individual cells by single-cell RNA sequencing (scRNA-seq) allows for a deeper understanding of cell types within a complex sample, like the COPD distal lung. ScRNA-seq data can be combined with cell-cell communication prediction tools to predict cellular interactions within a given sample; indeed, this approach was previously used to show evidence for increased endothelial CXCL signaling in COPD. more...

Organism:

Homo sapiens

Type:

Expression profiling by high throughput sequencing

Platform:

GPL24676

6 Samples

Download data: MTX, TSV