Data Analysis

The alignment of sequencing reads to a transcriptome is a common and important step in many RNA-seq analysis tasks. When aligning RNA-seq reads directly to a transcriptome (as is common in the de novo setting or when a trusted reference ...

The quantification of transcriptomic features is the basis of the analysis of RNA-seq data. Researchers at the Novartis Institutes for Biomedical Research have developed an integrated alignment workflow and a simple counting-based approach to derive estimates for gene, exon and ...

The use of high-throughput RNA sequencing to predict dynamic operon structures in prokaryotic genomes has recently gained popularity in bioinformatics. Researchers from the Finnish Institute of Occupational Health provide the R implementation of a novel method that uses transcriptomic features ...

Several R packages exist for the detection of differentially expressed genes from RNA-Seq data. The analysis process includes three main steps, namely normalization, dispersion estimation and test for differential expression. Quality control steps along this process are recommended but not ...

Single-cell technologies make it possible to quantify the comprehensive states of individual cells, and have the power to shed light on cellular differentiation in particular. Although several methods have been developed to fully analyze the single-cell expression data, there is ...

The growth plate (GP) comprising sequentially differentiated cell layers is a critical structure for bone elongation and regeneration. Although several key regulators in GP development have been identified using genetic perturbation, systematic understanding is still limited. Here, researchers from Tsinghua ...

A team led by researchers at the University of Washington has developed a new statistical method-MutRSeq-for detecting differentially expressed single nucleotide variants (SNVs) based on RNA-seq data. Specifically, we focus on nonsynonymous mutations and employ a hierarchical likelihood approach to jointly ...

Increased emphasis on reproducibility of published research in the last few years has led to the large-scale archiving of sequencing data. While this data can, in theory, be used to reproduce results in papers, it is typically not easily usable ...

Differential expression analysis (DEA) is one of the main instruments utilized for revealing molecular mechanisms in pathological and physiological conditions. DIANA-mirExTra v2.0 performs a combined DEA of mRNAs and microRNAs (miRNAs) to uncover miRNAs and transcription factors (TFs) playing important ...

The identification of microRNA (miRNA) target sites is fundamentally important for studying gene regulation. There are dozens of computational methods available for miRNA target site prediction. Despite their existence, we still cannot reliably identify miRNA target sites, partially due to ...