CLIP Tool Kit (CTK): pipeline, user interface and tutorials for CLIP data analysis

Columbia University Health Sciences, New York NY

Investigators

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Abstract

Project summary CLIP Tool Kit (CTK): software package, user interface and tutorials for CLIP data analysis Multiple steps of gene expression regulation rely on co- and post-transcriptional processing of RNA through its interaction with RNA-binding proteins (RBPs). UV cross-linking and immunoprecipitation (CLIP) of protein- RNA complexes, followed by high-throughput sequencing of isolated RNA, has become a gold standard for mapping in vivo protein-RNA interactions on a genome-wide scale. However, there remains a lack of software tools that provide flexible, streamlined and comprehensive analysis of CLIP data that incorporates the most recent technical advancements of CLIP protocols and sequencing technology. Here we propose to develop the CLIP Tool Kit (CTK) to fill this gap by building on our extensive experience in this field and enhancing a prototype we have developed for our research over the years. Taking raw sequence reads coming off sequencers as input, CTK will perform a series of analyses using its three major components: 1) quality filtering and mapping of raw reads, followed by a stringent, model-based algorithm to collapse PCR duplicates to obtain unique CLIP tags; 2) an adaptive valley-seeking algorithm to define CLIP tag clusters and perform peak calling; and 3) a statistical method to determine the exact protein-RNA crosslink sites through analysis of crosslink induced mutation sites (CIMS) and truncation sites (CITS). We will implement several novel algorithms as well as important extensions to our current software package, to make significant improvement in accuracy and efficiency, and to keep up with advancement in CLIP protocols and sequencing technologies. In addition, we aim to improve the usability and dissemination of the software. We will implement an interface through Galaxy so that CTK can be integrated into this widely used bioinformatics workflow management system. Multiple tutorials for typical analysis pipelines will be developed and a user group will be established. Thus, this study will provide a valuable resource for the RNA biology research community.