Tag Archives: read counts

Current approaches to single-cell transcriptomic analysis are computationally intensive and require assay-specific modeling which limit their scope and generality. Researchers from UC Berkely and Stanford University have developed a novel method that departs from standard analysis pipelines, comparing and clustering ...

Differential expression analysis of RNA sequencing (RNA-seq) data typically relies on reconstructing transcripts or counting reads that overlap known gene structures. Previously, researchers at Johns Hopkins Bloomberg School of Public Health introduced an intermediate approach called differentially expressed region (DER) finder ...

With the advances in high-throughput DNA sequencing technologies, RNA-seq has rapidly emerged as a powerful tool for the quantitative analysis of gene expression and transcript variant discovery. In comparative experiments, differential expression analysis is commonly performed on RNA-seq data to ...

Deep sequencing of small RNAs has become a routine process in recent years, but no dedicated viewer is as yet available to explore the sequence features simultaneously along with secondary structure and gene expression of microRNA (miRNA). A team led ...

Parseq is a statistical approach for transcription landscape reconstruction at a basepair resolution from RNA Seq read counts. It is based on a state-space model which describes, in terms of abrupt shifts and more progressive drifts, the transcription level dynamics ...

In the last decade, Next-Generation Sequencing technologies have been extensively applied to quantitative transcriptomics, making RNA sequencing a valuable alternative to microarrays for measuring and comparing gene transcription levels. Although several methods have been proposed to provide an unbiased estimate ...