Yi Zhong | bioRxiv Science

bioRxiv2015

RiboDiff: Detecting Changes of Translation Efficiency from Ribosome Footprints

MotivationDeep sequencing based ribosome footprint profiling can provide novel insights into the regulatory mechanisms of protein translation. However, the observed ribosome profile is fundamentally confounded by transcriptional activity. In order to decipher principles of translation regulation, tools that can reliably detect changes in translation efficiency in case-control studies are needed.\n\nResultsWe present a statistical framework and analysis tool, RiboDiff, to detect genes with changes in translation efficiency across experimental treatments. RiboDiff uses generalized linear models to estimate the over-dispersion of RNA-Seq and ribosome profiling measurements separately, and performs a statistical test for differential translation efficiency using both mRNA abundance and ribosome occupancy.\n\nAvailabilityRiboDiff webpage http://bioweb.me/ribodiff. Source code including scripts for preprocessing the FASTQ data are available at http://github.com/ratschlab/ribodiff.\n\nContactzhongy@cbio.mskcc.org and Gunnar.Ratsch@ratschlab.org.

Bioinformatics↗

bioRxiv2015

SplAdder: Identification, quantification and testing of alternative splicing events from RNA-Seq data

Motivation: Understanding the occurrence and regulation of alternative splicing (AS) is a key task towards explaining the regulatory processes that shape the complex transcriptomes of higher eukaryotes. With the advent of high-throughput sequencing of RNA (RNA-Seq), the diversity of AS transcripts could be measured at an unprecedented depth. Although the catalog of known AS events has grown ever since, novel transcripts are commonly observed when working with less well annotated organisms, in the context of disease, or within large populations. Whereas an identification of complete transcripts is technically challenging and computationally expensive, focusing on single splicing events as a proxy for transcriptome characteristics is fruitful and sufficient for a wide range of analyses.\n\nResults: We present SplAdder, an alternative splicing toolbox, that takes RNA-Seq alignments and an annotation file as input to i) augment the annotation based on RNA-Seq evidence, ii) identify alternative splicing events present in the augmented annotation graph, iii) quantify and confirm these events based on the RNA-Seq data, and iv) test for significant quantitative differences between samples. Thereby, our main focus lies on performance, accuracy and usability.\n\nAvailability: Source code and documentation are available for download at http://github.com/ratschlab/spladder. Example data, introductory information and a small tutorial are accessible via http://bioweb.me/spladder.\n\nContact: andre.kahles@ratschlab.org, gunnar.ratsch@ratschlab.org

Bioinformatics↗