Yeo Lab Software
BENTO
Our new Python toolkit for subcellular analysis of spatial transcriptomics data. Developed by Clarence Mah and Noorsher Ahmed. Github, Publication
SKIPPER
Our new end-to-end workflow that converts unprocessed CLIP-seq reads into annotated binding sites using an improved statistical framework. Developed by Evan Boyle and Charlene Her. Github, Publication.
HydRA
A deep-learning model for predicting RNA-binding capacity of proteins from protein interaction association context and protein sequence. Developed by Wenhao Jin and Kris Brannan. Github, Publication.
FLARE
Our new Snakemake-based pipeline that uses a statistical approach to determine regions of enriched RNA editing, using SAILOR-derived editing sites as a starting point. Developed by Eric Kofman and Brian Yee. Github, Publication.
RBP Maps
A tool to generate RNA splicing regulatory maps for RNA binding proteins by integrating CLIP and knock-down RNA-seq data. Developed by Brian Yee. Github, Publication.
A list of our most popular software tools. All our tools with code can be found in the Yeo Lab GitHub repository. Please contact Gene Yeo or Brian Yee for more information or troubleshooting help.
GENE YEO’S ALGORITHMS
eCLIP
A integrated CWL workflow that processes eCLIP fastq files to call enriched peak regions with CLIPPER and uses size-matched input samples to normalize and calculate fold-change enrichment within peaks. Developed by Brian Yee. Github
CLIPPER
Our original tool to identify CLIP-seq peaks. Developed by Mike Lovci. Github, PyPI, Publication
SAILOR
A CWL+Singularity implementation of an RNA editing workflow that predicts adenosine to inosine edits from RNA-seq data. Developed by Boyko Kakaradov and Brian Yee. Github, Publication.
Mudskipper
Our new end-to-end workflow that identifies RBP binding sites on RNA from antibody-barcode eCLIP and other multiplexed CLIP data. Developed by Charlene Her and Evan Boyle. Github.
SONAR
Our initial deep-learning model for predicting RNA-binding capacity of proteins from protein interaction association context and protein sequence. Developed by Wenhao Jin and Kris Brannan. Github, Publication.
CRaft-ID
An experimental and computational workflow for pooled CRISPR-Cas9 screening of image-based phenotypes using Cell Microsystem microRaft arrays. Developed by Emily Wheeler and Anthony Vu. Github, Publication.