Data Analysis

RNA sequencing (RNA-seq) experiments now span hundreds to thousands of samples. A source of frustration for investigators analyzing a given dataset is the inability to rapidly and reproducibly align its samples jointly. Current spliced alignment software is designed to analyze ...

Searching for RNA sequence-structure patterns is becoming an essential tool for RNA practitioners. Novel discoveries of regulatory non-coding RNAs in targeted organisms and the motivation to find them across a wide range of organisms have prompted the use of computational ...

As sequencing costs are being lowered continuously, RNA-seq has gradually been adopted as the first choice for comparative transcriptome studies with bacteria. Unlike microarrays, RNA-seq can directly detect cDNA derived from mRNA transcripts at a single nucleotide resolution. Not only ...

The past two decades of microRNA (miRNA) research has solidified the role of these small non-coding RNAs as key regulators of many biological processes and promising biomarkers for disease. The concurrent development in high-throughput profiling technology has further advanced our ...

NASB2015 Lecture 21- RNA seq Analysis with STAR In this lecture Yan Kou from the Ma’ayan Lab demonstrates how to run the popular genome aligner STAR for RNA-seq analysis

The emergence of next-generation high-throughput RNA sequencing (RNA-Seq) provides tremendous opportunities for researchers to analyze alternative splicing on a genome-wide scale. However, accurate identification of alternative splicing events from RNA-Seq data has remained an unresolved challenge in next-generation sequencing (NGS) ...

During gene expression, protein-coding transcripts are shaped by multiple processing events: 5′ end capping, pre-mRNA splicing, RNA editing, and 3′ end cleavage and polyadenylation. These events are required to produce mature mRNA, which can be subsequently translated. Nearly all of ...

Statistical methods development for differential expression analysis of RNA sequencing (RNA-seq) requires software tools to assess accuracy and error rate control. Since true differential expression status is often unknown in experimental datasets, artificially-constructed datasets must be utilized, either by generating ...

Flowering plants, also known as angiosperms, add an allure to the world that is unlike anything else in nature, but more importantly, they sustain us. Most of the fruits, vegetables, grains, beans, nuts, and even herbs and spices that we ...

Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to ...