Chemical map-based prediction of nucleosome positioning using the Bioconductor package nuCpos.

BMC Bioinformatics
Hiroaki KatoTakeshi Urano

Abstract

Assessing the nucleosome-forming potential of specific DNA sequences is important for understanding complex chromatin organization. Methods for predicting nucleosome positioning include bioinformatics and biophysical approaches. An advantage of bioinformatics methods, which are based on in vivo nucleosome maps, is the use of natural sequences that may contain previously unknown elements involved in nucleosome positioning in vivo. The accuracy of such prediction attempts reflects the genomic coordinate resolution of the nucleosome maps applied. Nucleosome maps are constructed using micrococcal nuclease digestion followed by high-throughput sequencing (MNase-seq). However, as MNase has a strong preference for A/T-rich sequences, MNase-seq may not be appropriate for this purpose. In addition to MNase-seq-based maps, base pair-resolution chemical maps of in vivo nucleosomes from three different species (budding and fission yeasts, and mice) are currently available. However, these chemical maps have yet to be integrated into publicly available computational methods. We developed a Bioconductor package (named nuCpos) to demonstrate the superiority of chemical maps in predicting nucleosome positioning. The accuracy of chemical map-bas...Continue Reading

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Citations

Dec 3, 2021·Nature Communications·Ashish Kumar SinghFelix Mueller-Planitz

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Software Mentioned

predNuCpos
R
CRAN
Biostrings
predNuPoP
Dyad
rasterVis
nuCpos
mutNuCpos
NuPoP

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