MOTIVATION: DNA methylation is important for gene silencing and imprinting in 
both plants and animals. Recent advances in bisulfite sequencing allow detection 
of single nucleotide variations (SNVs) achieving high sensitivity, but 
accurately identifying heterozygous SNVs from partially C-to-T converted 
sequences remains challenging.
RESULTS: We designed two methods, BayesWC and BinomWC, that substantially 
improved the precision of heterozygous SNV calls from ∼80% to 99% while 
retaining comparable recalls. With these SNV calls, we provided functions for 
allele-specific DNA methylation (ASM) analysis and visualizing the methylation 
status on reads. Applying ASM analysis to a previous dataset, we found that an 
average of 1.5% of investigated regions showed allelic methylation, which were 
significantly enriched in transposon elements and likely to be shared by the 
same cell-type. A dynamic fragment strategy was utilized for DMR analysis in 
low-coverage data and was able to find differentially methylated regions (DMRs) 
related to key genes involved in tumorigenesis using a public cancer dataset. 
Finally, we integrated 40 applications into the software package CGmapTools to 
analyze DNA methylomes. This package uses CGmap as the format interface, and 
designs binary formats to reduce the file size and support fast data retrieval, 
and can be applied for context-wise, gene-wise, bin-wise, region-wise and 
sample-wise analyses and visualizations.
AVAILABILITY AND IMPLEMENTATION: The CGmapTools software is freely available at 
https://cgmaptools.github.io/.
CONTACT: guoweilong@cau.edu.cn.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics 
online.