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Taudt, A.* ; Roquis, D.* ; Vidalis, A.* ; Wardenaar, R.* ; Johannes, F.* ; Colomé-Tatché, M.

METHimpute: Imputation-guided construction of complete methylomes from WGBS data.

BMC Genomics 19:444 (2018)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Background: Whole-genome bisulfite sequencing (WGBS) has become the standard method for interrogating plant methylomes at base resolution. However, deep WGBS measurements remain cost prohibitive for large, complex genomes and for population-level studies. As a result, most published plant methylomes are sequenced far below saturation, with a large proportion of cytosines having either missing data or insufficient coverage. Results: Here we present METHimpute, a Hidden Markov Model (HMM) based imputation algorithm for the analysis of WGBS data. Unlike existing methods, METHimpute enables the construction of complete methylomes by inferring the methylation status and level of all cytosines in the genome regardless of coverage. Application of METHimpute to maize, rice and Arabidopsis shows that the algorithm infers cytosine-resolution methylomes with high accuracy from data as low as 6X, compared to data with 60X, thus making it a cost-effective solution for large-scale studies. Conclusions: METHimpute provides methylation status calls and levels for all cytosines in the genome regardless of coverage, thus yielding complete methylomes even with low-coverage WGBS datasets. The method has been extensively tested in plants, but should also be applicable to other species. An implementation is available on Bioconductor.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Hidden Markov Model ; Imputation ; Methylation ; Whole-genome Bisulfite Sequencing; Cell-line Thp-1; In-vitro; Hacat Keratinocytes; Alkaloid Berberine; Dendritic Cells; Injury; Skin; Sensitization; Expression; Toxicity
Sprache englisch
Veröffentlichungsjahr 2018
HGF-Berichtsjahr 2018
ISSN (print) / ISBN 1471-2164
e-ISSN 1471-2164
Zeitschrift BMC Genomics
Quellenangaben Band: 19, Heft: 1, Seiten: , Artikelnummer: 444 Supplement: ,
Verlag BioMed Central
Verlagsort Elsevier House, Brookvale Plaza, East Park Shannon, Co, Clare, 00000, Ireland
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-554200-001
DOI 10.1186/s12864-018-4641-x
WOS ID WOS:000434664000003
Scopus ID 85048280464
PubMed ID 29879918
Erfassungsdatum 2018-07-09
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