Single-cell RNA-Seq Gaining Steam

rna-seq New computational tool enables powerful molecular analysis of biomedical tissue samples (5/14/2019)- Stanford researchers have developed a computational platform for analyzing the molecular behavior of individual cells in tissue samples,...
rna-seq A Bayesian mixture model for clustering droplet-based single-cell transcriptomic data from population studies (5/10/2019)- The recently developed droplet-based single-cell transcriptome sequencing (scRNA-seq) technology makes it feasible to perform a population-scale scRNA-seq study, in which the transcriptome is measured...
rna-seq Palantir – characterization of cell fate probabilities in single-cell data (5/1/2019)- Single-cell RNA sequencing studies of differentiating systems have raised fundamental questions regarding the discrete versus continuous nature of both differentiation and cell fate. Researchers from Memorial Sloan Kettering Cancer Center present Palantir, an algorithm that models trajectories of differentiating cells by treating cell fate as a probabilistic process and leverages entropy to measure cell plasticity ...
rna-seq Scone – performance assessment and selection of normalization procedures for single-cell RNA-Seq (4/30/2019)- Systematic measurement biases make normalization an essential step in single-cell RNA sequencing (scRNA-seq) analysis. There may be multiple competing considerations behind the assessment of normalization performance, of which some may be study specific. Researchers at UC Berkeley have developed “scone”- a flexible framework for assessing performance based on a comprehensive panel of data-driven metrics. Through ...
rna-seq scClustViz – Single-cell RNAseq cluster assessment and visualization (4/26/2019)- Single-cell RNA sequencing (scRNAseq) represents a new kind of microscope that can measure the transcriptome profiles of thousands of individual cells from complex cellular mixtures, such as in a tissue, in a single experiment. This technology is...
rna-seq New genomics tool ECCITE-seq expands multimodal single cell analysis (4/23/2019)- A new technique called ECCITE-seq, developed by scientists at the New York Genome Center’s (NYGC) Technology Innovation Lab (@NYGCtech), allows researchers to perform high-throughput measurements of multiple modalities of information from single cells. The technique, ECCITE-seq, published today in Nature Methods, stands for Expanded CRISPR-compatible Cellular Indexing of Transcriptomes and Epitopes by sequencing. ECCITE-seq profiles different types of biomolecules from thousands of single cells ...
rna-seq 1CellBio Announces Custom Targeted Bead Program to Accelerate Next Phase in Single-Cell Analysis (4/18/2019)- 1CellBio today announced a new program to supply select customers with its proprietary inDrop™ hydrogel beads synthesized with custom primers that target user-specified transcripts. “This new program enables researchers to focus their sequencing depth on their genes of interest rather than the full transcriptome,” said Colin J.H. Brenan, PhD, Chief Executive Officer at 1CellBio. “We ...
rna-seq scFBA – integration of single-cell RNA-seq data into population models to characterize cancer metabolism (4/2/2019)- Metabolic reprogramming is a general feature of cancer cells. Regrettably, the comprehensive quantification of metabolites in biological specimens does not promptly translate into knowledge on the utilization of metabolic pathways. By estimating fluxes across metabolic pathways, computational models hold the promise to bridge this gap between data and biological functionality. These models currently portray the ...
rna-seq Single cell combinatorial indexing reveals a landscape of mammalian development (3/19/2019)- New technology enables single cell analysis of mouse embryonic development Scientists from Seattle and Berlin have published an atlas on mouse embryonic...
A component overlapping attribute clustering (COAC) algorithm for single-cell RNA sequencing data analysis and potential pathobiological implications (3/14/2019)- Recent advances in next-generation sequencing and computational technologies have enabled routine analysis of large-scale single-cell ribonucleic acid sequencing (scRNA-seq) data. However, scRNA-seq technologies have suffered from several technical challenges, including low mean expression levels...

A slew of recent high profile papers and upcoming conferences highlight the growing interest in single-cell transcriptomics.