摘要：Chromatin loops represent one of the major levels of hierarchical folding of the genome. Although the situation is evolving, current methods have various difficulties with the accurate mapping of loops even in mammalian Hi-C data, and most of them fail to identify chromatin loops in animal species with substantially different genome architecture. This paper presents the loop and significant contact annotation (LASCA) pipeline, which uses Weibull distribution-based modeling to effectively identify loops and enhancer-promoter interactions in Hi-C data from evolutionarily distant species: from yeast and worms to mammals. Available at: https://github.com/ArtemLuzhin/LASCA_pipeline .
其他摘要：Abstract Chromatin loops represent one of the major levels of hierarchical folding of the genome. Although the situation is evolving, current methods have various difficulties with the accurate mapping of loops even in mammalian Hi-C data, and most of them fail to identify chromatin loops in animal species with substantially different genome architecture. This paper presents the loop and significant contact annotation (LASCA) pipeline, which uses Weibull distribution-based modeling to effectively identify loops and enhancer–promoter interactions in Hi-C data from evolutionarily distant species: from yeast and worms to mammals. Available at: https://github.com/ArtemLuzhin/LASCA_pipeline .
