HiCRes: a computational method to estimate and predict the genomic resolution of Hi-C libraries
Claire Marchal, Nivedita Singh, Ximena Corso‐Díaz, Anand Swaroop
Abstract
Three-dimensional (3D) conformation of the chromatin is crucial to stringently regulate gene expression patterns and DNA replication in a cell-type specific manner. Hi-C is a key technique for measuring 3D chromatin interactions genome wide. Estimating and predicting the resolution of a library is an essential step in any Hi-C experimental design. Here, we present the mathematical concepts to estimate the resolution of a dataset and predict whether deeper sequencing would enhance the resolution. We have developed HiCRes, a docker pipeline, by applying these concepts to several Hi-C libraries.
Topics & Concepts
BiologyChromatinComputational biologyPipeline (software)Resolution (logic)GenomeDNAReplication (statistics)DNA sequencingGenomic libraryGeneticsGeneBase sequenceComputer scienceArtificial intelligenceVirologyProgramming languageGenomics and Chromatin DynamicsChromosomal and Genetic VariationsGenomic variations and chromosomal abnormalities