Affiliation:
1. Division of Experimental Parasitology, Faculty of Veterinary Medicine, Ludwig-Maximilians-Universität München , Munich , Germany
2. Biomedical Center, Division of Physiological Chemistry, Faculty of Medicine, Ludwig-Maximilians-Universität München , Munich , Germany
Abstract
Abstract
Nucleic acid interactome data, such as chromosome conformation capture data and RNA–DNA interactome data, are currently analyzed via pipelines that must be rerun for each new parameter set. A more dynamic approach is desirable since the optimal parameter set is commonly unknown ahead of time and rerunning pipelines is a time-consuming process. We have developed an approach fast enough to process interactome data on-the-fly using a sparse prefix sum index. With this index, we created Smoother, a flexible, multifeatured visualization and analysis tool that allows interactive filtering, e.g. by mapping quality, almost instant comparisons between different normalization approaches, e.g. iterative correction, and ploidy correction. Further, Smoother can overlay other sequencing data or genomic annotations, compare different samples, and perform virtual 4C analysis. Smoother permits a novel way to interact with and explore interactome data, fostering comprehensive, high-quality data analysis. Smoother is available at https://github.com/Siegel-Lab/BioSmoother under the MIT license.
Funder
German Research Foundation
ERC Starting Grant
ERC Consolidator Grant
Publisher
Oxford University Press (OUP)