ArticleBMC bioinformatics2015
BSPAT: a fast online tool for DNA methylation co-occurrence pattern analysis based on high-throughput bisulfite sequencing data.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed, 31 citations in OpenAlex.
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- Methylation patterns at the adjacent CpG sites within enhancers are a part of cell identity.Epigenetics & chromatin · 2024Article
- Epigenetic tumor heterogeneity in the era of single-cell profiling with nanopore sequencing.Clinical epigenetics · 2022Review
- A 13-Gene DNA Methylation Analysis Using Oral Brushing Specimens as an Indicator of Oral Cancer Risk: A Descriptive Case Report.Diagnostics (Basel, Switzerland) · 2022Article
- MethPanel: a parallel pipeline and interactive analysis tool for multiplex bisulphite PCR sequencing to assess DNA methylation biomarker panels for disease detection.Bioinformatics (Oxford, England) · 2021Article
- Evaluating the Consistency of Gene Methylation in Liver Cancer Using Bisulfite Sequencing Data.Frontiers in cell and developmental biology · 2021Article
- Pre-Operative Evaluation of DNA Methylation Profile in Oral Squamous Cell Carcinoma Can Predict Tumor Aggressive Potential.International journal of molecular sciences · 2020Article
- Modeling DNA Methylation Profiles through a Dynamic Equilibrium between Methylation and Demethylation.Biomolecules · 2020Article
- DNMT1 mutations leading to neurodegeneration paradoxically reflect on mitochondrial metabolism.Human molecular genetics · 2020Article
- Application of a non-invasive oral brushing procedure based on bisulfite sequencing of a 13-gene panel to study high-risk OSCC patients.Cancer biomarkers : section A of Disease markers · 2020Observational
- Methylation Profile of X-Chromosome-Related Genes in Male Breast Cancer.Frontiers in oncology · 2020Article
- 13-gene DNA Methylation Analysis from Oral Brushing: A Promising Non Invasive Tool in the Follow-up of Oral Cancer Patients.Journal of clinical medicine · 2019Article
- EPIC-TABSAT: analysis tool for targeted bisulfite sequencing experiments and array-based methylation studies.Nucleic acids research · 2019Article
- A survey of the approaches for identifying differential methylation using bisulfite sequencing data.Briefings in bioinformatics · 2018Review
- Development and application of an integrated allele-specific pipeline for methylomic and epigenomic analysis (MEA).BMC genomics · 2018Article
- CpG location and methylation level are crucial factors for the early detection of oral squamous cell carcinoma in brushing samples using bisulfite sequencing of a 13-gene panel.Clinical epigenetics · 2017Article
- Profiling genome-wide DNA methylation.Epigenetics & chromatin · 2016Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundBisulfite sequencing is one of the most widely used technologies in analyzing DNA methylation patterns, which are important in understanding and characterizing the mechanism of DNA methylation and its functions in disease development. Efficient and user-friendly tools are critical in carrying out such analysis on high-throughput bisulfite sequencing data. However, existing tools are either not scalable well, or inadequate in providing visualization and other desirable functionalities.
resultsIn order to handle ultra large sequencing data and to provide additional functions and features, we have developed BSPAT, a fast online tool for bisulfite sequencing pattern analysis. With a user-friendly web interface, BSPAT seamlessly integrates read mapping/quality control/methylation calling with methylation pattern generation and visualization. BSPAT has the following important features: 1) instead of using multiple/pairwise sequence alignment methods, BSPAT adopts an efficient and widely used sequence mapping tool to provide fast alignment of sequence reads; 2) BSPAT summarizes and visualizes DNA methylation co-occurrence patterns at a single nucleotide level, which provide valuable information in understanding the mechanism and regulation of DNA methylation; 3) based on methylation co-occurrence patterns, BSPAT can automatically detect potential allele-specific methylation (ASM) patterns, which can greatly enhance the detection and analysis of ASM patterns; 4) by linking directly with other popular databases and tools, BSPAT allows users to perform integrative analysis of methylation patterns with other genomic features together within regions of interest.
conclusionBy utilizing a real bisulfite sequencing dataset generated from prostate cancer cell lines, we have shown that BSPAT is highly efficient. It has also reported some interesting methylation co-occurrence patterns and a potential allele-specific methylation case. In conclusion, BSPAT is an efficient and convenient tool for high-throughput bisulfite sequencing data analysis that can be broadly used.
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