SVIM: Structural Variant Identification using Mapped Long Reads
SVIM detects and characterizes structural variants from long-read sequencing data, outperforming existing tools on simulated and real datasets.
Author
Max Planck Institute for Molecular GeneticsORCID 0000-0002-1765-4241Unclaimed ORCID profile · follow to get notified of new preprints
38 papers
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SVIM detects and characterizes structural variants from long-read sequencing data, outperforming existing tools on simulated and real datasets.
Stefanie Schöne, Melissa Bothe, Edda Einfeldt…·Sebastiaan H. Meijsing
This study develops synSTARR-seq to analyze how DNA sequence and shape affect transcriptional activity and noise using synthetic GR binding sites.
Luigi Grassi, Farzin Pourfarzad, Sebastian Ullrich…·Taco W Kuijpers
The paper maps the epigenomic and functional changes during human neutrophil differentiation from bone marrow progenitors to mature cells, revealing key regulatory mechanisms.
Daniel Rico, Joost H.A. Martens, Kate Downes…·Hendrik G. Stunnenberg
This study compares the epigenomes of neutrophils and monocytes to identify regulatory elements and chromatin states, revealing differences in enhancer activity and DNA methylation.
David Heller, Ralf Krestel, Uwe Ohler…·Annalisa Marsico
ssHMM identifies sequence-structure motifs for RNA-binding proteins using a hidden Markov model and Gibbs sampling, outperforming existing tools in accuracy and speed.
Jun Yang, M-Hossein Moeinzadeh, Heiner Kuhl…·Martin Vingron
This paper presents a half haplotype-resolved genome of hexaploid Ipomoea batatas, revealing two ancient whole genome duplication events and specialized compound biosynthesis gene clusters.
David Juan, Juliane Perner, Enrique Carrillo de Santa Pau…·Alfonso Valencia
The paper identifies 5hmC as a central hub in the chromatin network of ESCs, linking DNA demethylation to chromatin remodeling and pluripotency factors through epigenomic co-localization and co-evolution analysis.
Juliane Perner, Julia Lasserre, Sarah Kinkley…·Ho-Ryun Chung
The paper infers interactions between chromatin modifiers and histone modifications from ChIP-Seq data, identifying known and novel interactions that contribute to understanding chromatin-signaling networks.