Expression and Quantification

Single cell transcriptomics is critical for understanding cellular heterogeneity and identification of novel cell types. Leveraging the recent advances in single cell RNA sequencing (scRNA-Seq) technology requires novel unsupervised...

MicroRNAs (miRNAs) function as master regulators of gene expression. Recent studies demonstrate that miRNA isoforms (isomiRs) play a unique role during cancer development. National Cancer Institute researchers have developed QuagmiR, the first cloud...

Single-cell RNA-sequencing (scRNA-seq) has brought the study of the transcriptome to higher resolution and makes it possible for scientists to provide...

Clustering of genes and/or samples is a common task in gene expression analysis. The goals in clustering can vary, but an important scenario is that of...

Advances in high-throughput sequencing on single-cell gene expressions [single-cell RNA sequencing (scRNA-seq)] have enabled transcriptome profiling on individual cells from complex samples. A common goal in scRNA-seq data...

Single-cell RNA sequencing (scRNA-seq) is a powerful tool to study heterogeneity and dynamic changes in cell populations. Clustering scRNA-seq is essential in identifying new cell types and studying their characteristics. University of Pennsylvania...

Whole transcriptome studies typically yield large amounts of data, with expression values for all genes or transcripts of the genome. The search for genes...

Differential gene expression (DGE) analysis is one of the most common applications of RNA-sequencing (RNA-seq) data. This process allows for the elucidation of differentially expressed genes across two or more conditions and is widely used in many...

Full-length isoform sequencing has advanced our knowledge of isoform biology. However, apart from applying full-length isoform sequencing to very few single cells, isoform sequencing has been limited...

Recent single-cell RNA-seq protocols based on droplet microfluidics use massively multiplexed barcoding to enable simultaneous measurements of transcriptomes for thousands of individual cells. The increasing complexity of such data creates challenges for subsequent computational processing...