Data Analysis

Double-stranded RNAs (dsRNAs) are potent triggers of innate immune responses upon recognition by cytosolic dsRNA sensor proteins. Identification of...

Single-cell RNA sequencing (scRNA-seq) technologies have rapidly developed in recent years. The droplet-based single cell platforms enable the profiling of gene expression in tens of thousands of...

What is scRNA-Seq Quantification? The first step for any Single-cell RNA-Seq analysis is to perform the quantification or, in other words, to obtain the gene expression values by cell. It is the input data for further analysis like Clustering, Trajectory, ...

CITE-seq (cellular indexing of transcriptomes and epitopes) is an RNA sequencing-based method that simultaneously quantifies cell surface protein and...

Benchmarking single-cell RNA-seq (scRNA-seq) and single-cell Assay for Transposase-Accessible Chromatin using sequencing (scATAC-seq) computational tools demands simulators to...

Pediatric acute myeloid leukemia (pAML) is characterized by heterogeneous cellular composition, driver alterations and prognosis. Characterization of this heterogeneity and how it affects treatment response remains understudied in pediatric patients. Researchers at the Michael Smith Genome Sciences Centre used single-cell ...

To understand the biological impact of alternative pre-mRNA splicing, it is vital to know which exons are involved, what protein domains they encode...

Ribosome profiling (Ribo-Seq) captures a “snapshot” of ribosomes’ locations at the entire transcriptome of a cell at sub-codon resolution providing insights...

Many tools and algorithms are available for analyzing transcriptomics data. These include algorithms for performing sequence alignment, data normalization and imputation, clustering, identifying differentially...

To gain a better understanding of the complexity of gene expression in normal and diseased tissues it is important to account for the spatial context and identity of cells in situ...