Single-Cell Analysis: Applications and Resolutions for Research
In brief
There are a number of applications for single-cell research.
Some of the main applications include:
- identification of gene expression profiles for novel subpopulations
- identification of cell populations with altered states, associated with survival or drug response
- comparison of cell type composition of samples across different conditions
- identification of novel cell subpopulations.
In this whitepaper we discuss applications, challenges, and resolutions for using single-cell data in research, alongside what is expected in the future in this area of analysis.
Request a bioinformatics analysis sample for Single-Cell RNAseq
This report describes the analysis of a single-cell RNA sequencing (scRNA-seq) dataset containing peripheral blood mononuclear cell (PBMC) gene expression profiles sampled from a healthy donor. This dataset was obtained from the publicly available 10X Genomics download portal.
The main objectives of this analysis were to:
- Identify cell clusters in the data and annotate these by immune cell type using established biomarkers.
- Identify differentially expressed genes (DEGs) between cell populations.
- Identify functional pathways that are significantly enriched in DEGs between clusters.
The report has been created to showcase our data analysis reports and capabilities in Single-Cell RNAseq analysis.
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