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LuxUS: DNA methylation analysis using generalized linear mixed model with spatial correlation
MOTIVATION: DNA methylation is an important epigenetic modification, which has multiple functions. DNA methylation and its connections to diseases have been extensively studied in recent years. It is known that DNA methylation levels of neighboring cytosines are correlated and that differential DNA...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750928/ https://www.ncbi.nlm.nih.gov/pubmed/32484876 http://dx.doi.org/10.1093/bioinformatics/btaa539 |
Sumario: | MOTIVATION: DNA methylation is an important epigenetic modification, which has multiple functions. DNA methylation and its connections to diseases have been extensively studied in recent years. It is known that DNA methylation levels of neighboring cytosines are correlated and that differential DNA methylation typically occurs rather as regions instead of individual cytosine level. RESULTS: We have developed a generalized linear mixed model, LuxUS, that makes use of the correlation between neighboring cytosines to facilitate analysis of differential methylation. LuxUS implements a likelihood model for bisulfite sequencing data that accounts for experimental variation in underlying biochemistry. LuxUS can model both binary and continuous covariates, and mixed model formulation enables including replicate and cytosine random effects. Spatial correlation is included to the model through a cytosine random effect correlation structure. We show with simulation experiments that using the spatial correlation, we gain more power to the statistical testing of differential DNA methylation. Results with real bisulfite sequencing dataset show that LuxUS is able to detect biologically significant differentially methylated cytosines. AVAILABILITY AND IMPLEMENTATION: The tool is available at https://github.com/hallav/LuxUS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
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