COVID-19 Cell-cell Communication Imputation based on Single-cell RNA-Sequencing Data Reveals Novel Immune Signals

Dongqing Li

2022

Abstract

Since its outbreak, the COVID-19 global pandemic had become one of the most serious diseases existed in the human history. Millions of people had been infected, and the pandemic is currently affecting the whole world in various fields such as public health, economy, and society. As a result, a better understanding of such disease is imminently needed to effectively control the ongoing pandemic. Cell-cell communications regulated by ligand-receptor pairs are crucial in coordinating diverse gene expression pathways. In a previous study, researchers implemented the single-cell RNA-sequencing technology on samples collected from COVID patients and healthy controls to obtain their cell-level RNA expression profiles. In this study, we statistically analyzed scRNA-seq data from a COVID patient and a healthy control generated by the previous study, and compared various gene expression between the samples with packages Scanpy and CellPhoneDB. Various plots were created to provide a comprehensive representation and comparison between the samples about gene expressions. The results showed numerous distinctions between the two sample in the overall gene expression level, the expression level of several immune-related ligand-receptor pairs across different cell type pairs, and the expression level of specific types of gene in different cell types. This study provided computational and statistical evidences related to COVID-19 pathology, which can be further pursued through biological experiments to obtain a better understanding of the global pandemic. The statistical analysis method used in this study showed an alternative way that can be potentially used to better understand the SARS-CoV-2 virus.

Paper Citation

in Harvard Style

Li D. (2022). COVID-19 Cell-cell Communication Imputation based on Single-cell RNA-Sequencing Data Reveals Novel Immune Signals. In Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics - Volume 1: ICBEB, ISBN 978-989-758-595-1, pages 889-896. DOI: 10.5220/0011312700003443

in Bibtex Style

@conference{icbeb22,
author={Dongqing Li},
title={COVID-19 Cell-cell Communication Imputation based on Single-cell RNA-Sequencing Data Reveals Novel Immune Signals},
booktitle={Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics - Volume 1: ICBEB,},
year={2022},
pages={889-896},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011312700003443},
isbn={978-989-758-595-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Biomedical Engineering and Bioinformatics - Volume 1: ICBEB,
TI - COVID-19 Cell-cell Communication Imputation based on Single-cell RNA-Sequencing Data Reveals Novel Immune Signals
SN - 978-989-758-595-1
AU - Li D.
PY - 2022
SP - 889
EP - 896
DO - 10.5220/0011312700003443