Work

Epigrahmm – epigenomic r-based analysis with hidden Markov models

Year: 2020

Type: other

Abstract: epigraHMM provides a comprehensive set of tools to flexibly analyze data from a wide range of bulk epigenomic assays. epigraHMM is optimized for genome-wide analyses and is efficient for the analysis under multi-sample multiple-condition settings, as well as consensus peak calling in multi-sample settings. epigraHMM utilizes modified versions of hidden Markov models that are robust to the diversity of peak profiles and are particularly useful for epigenomic marks that exhibit broad peaks. For multi-condition designs, epigraHMM allows the classification of differential peaks according to the observed differential combinatorial patterns of enrichment.

DOI: 10.7490/f1000research.1118042.1

Authors: Pedro Baldoni, Naim U. Rashid, Joseph G. Ibrahim

Institution: University of North Carolina at Chapel Hill

Language: English

Topic: Genomics and Chromatin Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

OpenAlex ID: W3044120253

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