Dataset Information

A Novel Method to Identify the Differences Between Two Single Cell Groups at Single Gene, Gene Pair, and Gene Module Levels.

ABSTRACT: Single-cell sequencing technology can not only view the heterogeneity of cells from a molecular perspective, but also discover new cell types. Although there are many effective methods on dropout imputation, cell clustering, and lineage reconstruction based on single cell RNA sequencing (RNA-seq) data, there is no systemic pipeline on how to compare two single cell clusters at the molecular level. In the study, we present a novel pipeline on comparing two single cell clusters, including calling differential gene expression, coexpression network modules, and so on. The pipeline could reveal mechanisms behind the biological difference between cell clusters and cell types, and identify cell type specific molecular mechanisms. We applied the pipeline to two famous single-cell databases, Usoskin from mouse brain and Xin from human pancreas, which contained 622 and 1,600 cells, respectively, both of which were composed of four types of cells. As a result, we identified many significant differential genes, differential gene coexpression and network modules among the cell clusters, which confirmed that different cell clusters might perform different functions.

SUBMITTER: Cui L

PROVIDER: S-EPMC8005607 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Novel Method to Identify the Differences Between Two Single Cell Groups at Single Gene, Gene Pair, and Gene Module Levels.

Cui Lingyu L Wang Bo B Ren Changjing C Wang Ailan A An Hong H Liang Wei W

Frontiers in genetics 20210315

Single-cell sequencing technology can not only view the heterogeneity of cells from a molecular perspective, but also discover new cell types. Although there are many effective methods on dropout imputation, cell clustering, and lineage reconstruction based on single cell RNA sequencing (RNA-seq) data, there is no systemic pipeline on how to compare two single cell clusters at the molecular level. In the study, we present a novel pipeline on comparing two single cell clusters, including calling ...[more]

PMID: 33790951

Similar Datasets

Project description:Alzheimer's disease (AD) is the most common type of neurological disorder that results from brain cell death; however, not all brain regions are simultaneously affected to the same extent. Despite single biomarkers for AD having been determined on a genome‑wide scale, the differential co‑expression in gene pairs between regions and interactions with other types of cellular molecules, particularly non‑coding (nc)RNAs, are often overlooked in studies investigating the underlying mechanisms associated with AD. In the present study, based on 1,548 samples obtained from a cohort of 90 patients with AD spanning 19 brain regions, a gene‑pair based method was established for the classification of 19 brain regions into seven different groups, including marked disparate groupings of six single regions and a cluster of another 13 regions as revealed by principal component analysis (PCA). To further investigate the different underlying mechanisms associated with each group, five highly interconnected functional modules of the protein‑protein interaction network were demonstrated to characterize the seven region groups containing six single groups and 13 clustered regions based on 4,731 gene‑pairs. Genes in two of the functional modules exhibited a strong association with pathways associated with the nervous system, including cholinergic synapses, circadian entrainment and dopaminergic synapses. Notably, following integration of these two modules with a ncRNA‑mediated network, one module demonstrated a strong association with micro (mi)RNAs, which were revealed to interact with numerous long non‑coding (lnc)RNAs associated with AD, such as metastasis associated lung adenocarcinoma transcript 1 and taurine upregulated 1. This suggested that mRNAs and lncRNAs may represent competing endogenous RNAs for binding with miRNAs. Thus, these results indicated that the ncRNA‑mediated gene regulatory module detected by the established gene pair‑based method may further the understanding of underlying mechanisms associated with AD as well as aid the development of novel therapeutic strategies for the treatment of patients with AD.

Dataset Information

A Novel Method to Identify the Differences Between Two Single Cell Groups at Single Gene, Gene Pair, and Gene Module Levels.

Publications

A Novel Method to Identify the Differences Between Two Single Cell Groups at Single Gene, Gene Pair, and Gene Module Levels.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets