bioconductor-dmcfb
Differentially Methylated Cytosines via a Bayesian Functional Approach
Differentially Methylated Cytosines via a Bayesian Functional Approach
To install this package, run one of the following:
DMCFB is a pipeline for identifying differentially methylated cytosines using a Bayesian functional regression model in bisulfite sequencing data. By using a functional regression data model, it tries to capture position-specific, group-specific and other covariates-specific methylation patterns as well as spatial correlation patterns and unknown underlying models of methylation data. It is robust and flexible with respect to the true underlying models and inclusion of any covariates, and the missing values are imputed using spatial correlation between positions and samples. A Bayesian approach is adopted for estimation and inference in the proposed method.
Summary
Differentially Methylated Cytosines via a Bayesian Functional Approach
Last Updated
Dec 26, 2024 at 19:55
License
GPL-3
Total Downloads
17.0K
Supported Platforms