DNA methylation is an important epigenetic modification that plays a critical role in most eukaryotic organisms. Parental alleles in haploid genomes may exhibit different methylation patterns, which can lead to different phenotypes and even different therapeutic and drug responses to diseases. However, to our knowledge, no software is available for the identification of DNA methylation haplotype regions. In this paper, we developed a new method, MethHaplo, that identify DNA methylation haplotype regions with allele-specific DNA methylation and single nucleotide polymorphisms (SNPs) from whole-genome bisulfite sequencing (WGBS) data. Our results showed that methylation haplotype regions were ten times longer than haplotypes with SNPs only. When we integrate WGBS and high-throughput chromosome conformation capture (Hi-C) data, MethHaplo could call even longer haplotypes. By constructing methylation haplotypes for various cell lines, we provide a clearer picture of the effect of DNA methylation on gene expression, histone modification and three-dimensional chromosome structure at the haplotype level. Our method could benefit the study of parental inheritance-related disease and heterosis in agriculture.

Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing is a technology to study genome-wide long-range chromatin interactions bound by protein factors. NDID is a statistical technique for the joint normalization and differential chromatin interactions detection from ChIA-PET experiments.

Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing is a technology to study genome-wide long-range chromatin interactions bound by protein factors. ChIAMM is a statistical technique for processing and analyzing ChIA-PET sequence data using the Mixture model in the Bayesian framework.

DLO Hi-C Tool

DLO Hi-C Tool is a flexible and versatile pipeline for processing Digestion-Ligation-Only Hi-C data from raw sequencing reads to normalized contact maps and for providing quality controls for different steps. It includes more efficient iterative mapping and linker filtering. There are four main steps in DLO Hi-C Tool pipeline: pre-processing of raw sequencing reads, reads alignment and filtering, noise reduction and paired-end reads classification, and interaction visualization. It is available for users to flexibly modify any modules. Besides data processing, DLO Hi-C Tool also provides a graphical user interface and a HTML report.

Reference: Ping Hong, Hao Jiang, Weize Xu, Da Lin, Qian Xu, Gang Cao*, Guoliang Li*, The DLO Hi-C Tool for Digestion-Ligation-Only Hi-C Chromosome Conformation Capture Data Analysis, Genes 2020, 11(3), 289;

ChIA-PET Tool V3

Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing is a technology to study genome-wide long-range chromatin interactions bound by protein factors. ChIA-PET Tool V3, a software package for automatic processing of ChIA-PET sequence data, including:

  1. linker filtering
  2. mapping the paired-end reads to a reference genome
  3. purifying the mapped reads
  4. dividing the reads into different categories
  5. peak calling
  6. interaction calling
  7. visualizing the results

Reference: Guoliang Li*, Tongkai Sun, Huidan Chang, Liuyang Cai, Ping Hong, Qiangwei Zhou, Chromatin interaction analysis with updated ChIA-PET Tool (V3), Genes, 2019, 10, 554, also in bioRxiv 627257, doi: (2019)


BatMeth2 is an easy-use Bisulfite sequencing (BS-Seq) analysis pipeline tool, which can align BS reads with high accuracy while allowing for variable-length indels with respect to the reference genome. Additionally, BatMeth2 can calculate the methylation levels of individual loci, genomic regions or functional regions such as genes/transposable elements. Additional programs were also developed to provide methylation data annotation, visualization, and differentially methylated cytosine/region (DMC/DMR) detection. The whole package provides new tools and will benefit bisulfite data analysis. BatMeth2 improves DNA methylation calling, particularly for regions close to indels. It is an autorun package and easy to use. In addition, a DNA methylation visualization program and a differential analysis program are provided in BatMeth2.

Reference: Qiangwei Zhou, Jing-Quan Lim, Wing-Kin Sung*, Guoliang Li*, An Integrated Package for Bisulfite DNA Methylation Data Analysis with Indel-sensitive Mapping, BMC Bioinformatics, 2019, 20:47, DOI: 10.1186/s12859-018-2593-4 (22 January 2019)

ChromSDE: Inference of Spatial Organizations of Chromosomes Using Semi-definite Embedding Approach and Hi-C Data

For a long period of time, scientists studied genomes assuming they are linear. Recently, chromosome conformation capture (3C) based technologies, such as Hi-C, have been developed that provide the loci contact frequencies among loci pairs in a genome-wide scale. The technology unveiled that two far-apart loci can interact in the tested genome. It indicated that the tested genome forms a 3D chromsomal structure is to model the 3D chromosomal structure from the 3C-dervied data computationally. This paper presents a deterministic method called ChromSDE, which applies semi-definite programming techniques to find the best structure fitting the observed data and uses golden section search to find the correct parameter for converting the contact frequency to spatial distance. To the best of our knowledge, ChromSDE is the only method which can guarantee recovering the correct structure in the noise-free case. In addition, we prove that the parameter of conversion from contact frequency to spatial distance will change under different resolutions theoretically and empirically. Using simulation data and real Hi-C data, we show that ChromSDE is much more accurate and robust than existing methods. Finally, we demonstrate that interesting biological findings can be uncovered from our predicted 3D structure(Visit ChromSDE).

Reference: Zhizhuo Zhang, Guoliang Li, Kim-Chuan Toh and Wing-Kin Sung, 3D Chromosome Modeling with Semi-definite Programming and Hi-C Data, Journal of Computational Biology, 20, 831-846, 2013


ChIA-PET Tool is a software package for automatic processing of ChIA-PET sequence data, including linker filtering, mapping tags to reference genomes, identifying protein binding sites and chromatin interactions, and displaying the results on a graphical genome browser(Visit ChIA-PET Tool).

Reference: Guoliang Li#, M.J. Fullwood#, H. Xu#, F.H. Mulawadi, S. Velkov, V. Vega, P.N. Ariyaratne, Y.B. Mohamed, H.-S. Ooi, C. Tennakoon, C.-L. Wei, Y. Ruan, W.-K. Sung, ChIA-PET tool for comprehensive chromatin interaction analysis with paired-end tag sequencing, Genome Biology 11 (2) (2010) R22, DOI: 10.1186/gb-2010-1111-1182-r1122