hummingbird-package: A Bayesian Hidden Markov Model for the detection of...

Description Details Author(s) References


A package for identifying differentially methylated regions (DMRs) between case and control groups using whole genome bisulfite sequencing (WGBS) or reduced representative bisulfite sequencing (RRBS) experiment data.

The hummingbird package uses a Bayesian hidden Markov model (HMM) for detecting DMRs. It fits a Bayesian HMM for one chromosome at a time. The final output of hummingbird are the detected DMRs with start and end positions in a given chromosome, directions of the DMRs (hyper- or hypo-), and the numbers of CpGs in these DMRs.

The hummingbird package implements the algorithm described in the publication below.


The main functions of the package are: hummingbirdEM, hummingbirdPostAdjustment and hummingbirdGraph.


Eleni Adam, Tieming Ji, Desh Ranjan

Maintainer: Eleni Adam <>


Ji (2019) A Bayesian hidden Markov model for detecting differentially methylated regions. Biometrics 75(2):663-673.

hummingbird documentation built on April 18, 2021, 6 p.m.