Data Analysis

The B-cell receptor enables individual B cells to identify diverse antigens, including bacterial and viral proteins. While advances in RNA-seq have enabled high throughput profiling of transcript expression in single cells, the unique task of assembling the full-length heavy and ...

A new algorithm created at A*STAR allows scientists to track the trajectories of different cell lineages on the basis of their gene activity at the individual cell level. The tool, dubbed Mpath, should help reveal new insights into disease states ...

Next-generation sequencing technologies have profoundly impacted biology over recent years. Experimental protocols, such as photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP), which identifies protein-RNA interactions on a genome-wide scale, commonly employ deep sequencing. With PAR-CLIP, the incorporation of photoactivatable nucleosides into ...

The past decade has seen an exponential increase in biological sequencing capacity, and there has been a simultaneous effort to help organize and archive some of the vast quantities of sequencing data that are being generated. While these developments are ...

Perturbations in the environment lead to distinctive gene expression changes within a cell. Observed over time, those variations can be characterized by single impulse-like progression patterns. Researchers at the University of Bonn have developed ImpulseDE, an R package suited to ...

Single-cell RNA-seq (scRNA-seq) is increasingly used in a range of biomedical studies. Nonetheless, current RNA-seq analysis tools are not specifically designed to efficiently process scRNA-seq data due to their limited scalability. Here researchers from the Victor Chang Cardiac Research Institute ...

Although ultrahigh-throughput RNA-Sequencing has become the dominant technology for genome-wide transcriptional profiling, the vast majority of RNA-Seq studies typically profile only tens of samples, and most analytical pipelines are optimized for these smaller studies. However, projects are generating ever-larger data ...

The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. However, statistical methods often treat cellular heterogeneity as a nuisance. Researchers from the Dana-Farber Cancer Institute and the University of Wisconsin, Madison present a novel method to ...

Recent innovation of RNA-seq technology has shed insightful light on the transcriptomic evolution studies, especially on researches of tissue-specific expression evolution. Phylogenetic analysis of transcriptome data may help to identify causal gene expression differences underlying the evolutionary changes in morphological, ...

The individual sample heterogeneity is one of the biggest obstacles in biomarker identification for complex diseases such as cancers. Current statistical models to identify differentially expressed genes between disease and control groups often overlook the substantial human sample heterogeneity. Meanwhile, ...