Covering all your bases: incorporating intron signal from RNA-seq data

Intron-centric estimation of alternative splicing from RNA-seq data

MOTIVATION Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon-skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the majority of human splicing ev...

Covering all the bases.

Investigating the Function of Predicted Proteins from RNA-Seq Data in Holstein and Cholistani Cattle Breeds

This study was performed to determine the digital expression profile of different genes expressed in Holstein and Cholistani breeds as well as to evaluate the performance of predicted proteins derived from differentially expressed genes between these two breeds using RNA-Seq data. For this purpose, the whole mRNA sequence for a blood sample of American Holstein and Pakistani Cholistani cattle p...

Covering all the bases in academic medicine.

S1 Like all of my predecessors, I have spent a substantial amount of time during my year as President reviewing the addresses delivered by my extraordinarily distinguished predecessors and wondering how I could possibly say anything new, different, or in any way memorable. Like my more recent predecessors, my concerns about the quality of my Presidential Address were either compounded by, or pe...

iREAD: A Tool for Intron Retention Detection from RNA-seq data

Summary: Detecting intron retention (IR) events is emerging as a specialized need for RNA-seq data analysis. Here we present iREAD (intron REtention Analysis and Detector), a tool to detect IR events genome-wide from high-throughput RNA-seq data. The command line interface for iREAD is implemented in Python. iREAD takes as input an existing BAM file, representing the transcriptome, and a text f...