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Single-cell sequencing examines the nucleic acid sequence information from individual cells with optimized next-generation sequencing technologies, providing a higher resolution of cellular differences and a better understanding of the function of an individual cell in the context of its microenvironment. [1]
scLVM [117] scLVM is a modelling framework for single-cell RNA-seq data that can be used to dissect the observed heterogeneity into different sources, thereby allowing for the correction of confounding sources of variation. scM&T-Seq Parallel single-cell sequencing.
Detecting differences in gene expression level between two populations is used both single-cell and bulk transcriptomic data. Specialised methods have been designed for single-cell data that considers single cell features such as technical dropouts and shape of the distribution e.g. Bimodal vs. unimodal. [23]
Single-cell RNA sequencing (scRNA-Seq) provides the expression profiles of individual cells. Although it is not possible to obtain complete information on every RNA expressed by each cell, due to the small amount of material available, patterns of gene expression can be identified through gene clustering analyses .
Deconvolution of bulk sequencing experiments using single cell data Reference based Gene expression 2016 MuSiC [18] Cell-type Identification by estimating relative subsets of RNA transcripts Reference based Gene expression 2019 SCDC [30] Bulk gene expression deconvolution by multiple single-Cell RNA sequencing references Reference based
CITE-Seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing) is a method for performing RNA sequencing along with gaining quantitative and qualitative information on surface proteins with available antibodies on a single cell level. [1] So far, the method has been demonstrated to work with only a few proteins per cell.
Single-cell omics technologies has extended beyond the transcriptome to profile diverse physical-chemical properties at single-cell resolution, including whole genomes/exomes, DNA methylation, chromatin accessibility, histone modifications, epitranscriptome (e.g., mRNAs, microRNAs, tRNAs, lncRNAs), proteome, phosphoproteome, metabolome, and more.
G&T-seq (short for single cell genome and transcriptome sequencing) is a novel form of single cell sequencing technique allowing one to simultaneously obtain both transcriptomic and genomic data from single cells, allowing for direct comparison of gene expression data to its corresponding genomic data in the same cell...