The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. However, statistical methods often treat cellular heterogeneity as a nuisance. We present a novel method to characterize differences in expression in the presence of distinct expression states within and among biological conditions. We demonstrate that this framework can detect differential expression patterns under a wide range of settings. Compared to existing approaches, this method has higher power to detect subtle differences in gene expression distributions that are more complex than a mean shift, and can characterize those differences. The freely available R package scDD implements the approach.
Dr.seq2: A quality control and analysis pipeline for parallel single cell transcriptome and epigenome data
Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq data
A sparse differential clustering algorithm for tracing cell type changes via single-cell RNA-sequencing data
Identification of genes expressed in a mesenchymal subset regulating prostate organogenesis using tissue and single cell transcriptomics
Evaluating genetic causes of azoospermia: What can we learn from a complex cellular structure and single-cell transcriptomics of the human testis?
TWO-SIGMA: A novel two-component single cell model-based association method for single-cell RNA-seq data
DTWscore: differential expression and cell clustering analysis for time-series single-cell RNA-seq data
Elite control of HIV is associated with distinct functional and transcriptional signatures in lymphoid tissue CD8+ T cells
A clustering-independent method for finding differentially expressed genes in single-cell transcriptome data
Evaluating methods of inferring gene regulatory networks highlights their lack of performance for single cell gene expression data
Comparative analysis of differential gene expression analysis tools for single-cell RNA sequencing data
CellBIC: bimodality-based top-down clustering of single-cell RNA sequencing data reveals hierarchical structure of the cell type
CellSIUS provides sensitive and specific detection of rare cell populations from complex single-cell RNA-seq data
Coordinated host-pathogen transcriptional dynamics revealed using sorted subpopulations and single macrophages infected with Candida albicans
Monitoring early differentiation events in human embryonic stem cells by massively parallel signature sequencing and expressed sequence tag scan
The role of PI3K/AKT, MAPK/ERK and NFkappabeta signalling in the maintenance of human embryonic stem cell pluripotency and viability highlighted by transcriptional profiling and functional analysis
Permutation-based adjustments for the significance of partial regression coefficients in microarray data analysis
Tracing the derivation of embryonic stem cells from the inner cell mass by single-cell RNA-Seq analysis
A putative role for the immunoproteasome in the maintenance of pluripotency in human embryonic stem cells
Single cell profiling of circulating tumor cells: transcriptional heterogeneity and diversity from breast cancer cell lines
Emergence of bimodal cell population responses from the interplay between analog single-cell signaling and protein expression noise
SAMstrt: statistical test for differential expression in single-cell transcriptome with spike-in normalization
The dynamics and regulators of cell fate decisions are revealed by pseudotemporal ordering of single cells
Nonlinear signalling networks and cell-to-cell variability transform external signals into broadly distributed or bimodal responses
Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing
Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells
Single-cell mRNA sequencing identifies subclonal heterogeneity in anti-cancer drug responses of lung adenocarcinoma cells
Cell Checkpoints & Regulators
Cell cycle checkpoints are a series of complex checkpoint mechanisms that detect DNA abnormalities and ensure that DNA replication and repair are complete before cell division. They are primarily regulated by cyclins, cyclin-dependent kinases, and the anaphase-promoting complex/cyclosome. Here is the latest research.
Adult Stem Cells
Adult stem cells reside in unique niches that provide vital cues for their survival, self-renewal, and differentiation. They hold great promise for use in tissue repair and regeneration as a novel therapeutic strategies. Here is the latest research.