Single-cell RNA sequencing (scRNA-seq) is the sequencing of each cell's transcriptome to obtain gene expression patterns at a cellular resolution. Analysis of transcriptomes at the cellular level provides insights into the complex microenvironment of biological tissue. Unknown and rare cell types can be identified by scRNA-seq analysis. Single-cell RNA sequencing provides gene expression of each cell, which helps in differentiating between different cell types.

In this research work, the R software platform is used to analyze single-cell RNA sequencing dataset of COVID-19 with the help of certain software. Analysis provides information about the transcriptome. This research work focuses on analyzing single-cell RNA-seq data of PBMCs from COVID-19 patients on R platform. The dataset for the project work was taken from Gene Expression Omnibus - NCBI. The analysis includes several steps like pre-processing of the data, quality control, data correction, normalization, scaling, feature selection, dimensional reduction (PCA), clustering, marker identification, and cluster annotation.