@article{farrell2021,
  title = {{{BiSulfite Bolt}}: {{A}} Bisulfite Sequencing Analysis Platform},
  shorttitle = {{{BiSulfite Bolt}}},
  author = {Farrell, Colin and Thompson, Michael and Tosevska, Anela and Oyetunde, Adewale and Pellegrini, Matteo},
  year = {2021},
  month = may,
  journal = {Gigascience},
  volume = {10},
  number = {5},
  pages = {giab033},
  issn = {2047-217X},
  doi = {10.1093/gigascience/giab033},
  url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8106542/},
  urldate = {2024-09-12},
  abstract = {Background Bisulfite sequencing is commonly used to measure DNA methylation. Processing bisulfite sequencing data is often challenging owing to the computational demands of mapping a low-complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis-ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt), a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries. Findings We evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy. Conclusion BSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a Python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.},
  langid = {english},
  pmcid = {PMC8106542},
  pmid = {33966074},
  keywords = {DNA Methylation,High-Throughput Nucleotide Sequencing,Sequence Alignment,Sequence Analysis DNA,Software,Sulfites}
}

@article{krueger2011,
  title = {Bismark: A Flexible Aligner and Methylation Caller for {{Bisulfite-Seq}} Applications},
  shorttitle = {Bismark},
  author = {Krueger, Felix and Andrews, Simon R.},
  year = {2011},
  month = jun,
  journal = {Bioinformatics},
  volume = {27},
  number = {11},
  pages = {1571--1572},
  issn = {1367-4803},
  doi = {10.1093/bioinformatics/btr167},
  url = {https://doi.org/10.1093/bioinformatics/btr167},
  urldate = {2023-07-07},
  abstract = {Summary: A combination of bisulfite treatment of DNA and high-throughput sequencing (BS-Seq) can capture a snapshot of a cell's epigenomic state by revealing its genome-wide cytosine methylation at single base resolution. Bismark is a flexible tool for the time-efficient analysis of BS-Seq data which performs both read mapping and methylation calling in a single convenient step. Its output discriminates between cytosines in CpG, CHG and CHH context and enables bench scientists to visualize and interpret their methylation data soon after the sequencing run is completed.Availability and implementation: Bismark is released under the GNU GPLv3+ licence. The source code is freely available from www.bioinformatics.bbsrc.ac.uk/projects/bismark/.Contact: ~felix.krueger@bbsrc.ac.ukSupplementary information: ~Supplementary data are available at Bioinformatics online.}
}

@article{luo2018a,
  title = {Robust Single-Cell {{DNA}} Methylome Profiling with {{snmC-seq2}}},
  author = {Luo, Chongyuan and Rivkin, Angeline and Zhou, Jingtian and Sandoval, Justin P. and Kurihara, Laurie and Lucero, Jacinta and Castanon, Rosa and Nery, Joseph R. and {Pinto-Duarte}, Ant{\'o}nio and Bui, Brian and Fitzpatrick, Conor and O'Connor, Carolyn and Ruga, Seth and Van Eden, Marc E. and Davis, David A. and Mash, Deborah C. and Behrens, M. Margarita and Ecker, Joseph R.},
  year = {2018},
  month = sep,
  journal = {Nat Commun},
  volume = {9},
  number = {1},
  pages = {3824},
  issn = {2041-1723},
  doi = {10.1038/s41467-018-06355-2},
  abstract = {Single-cell DNA methylome profiling has enabled the study of epigenomic heterogeneity in complex tissues and during cellular reprogramming. However, broader applications of the method have been impeded by the modest quality of sequencing libraries. Here we report snmC-seq2, which provides improved read mapping, reduced artifactual reads, enhanced throughput, as well as increased library complexity and coverage uniformity compared to snmC-seq. snmC-seq2 is an efficient strategy suited for large-scale single-cell epigenomic studies.},
  langid = {english},
  pmcid = {PMC6147798},
  pmid = {30237449},
  keywords = {Adult,Animals,Dimerization,DNA Methylation,Gene Library,Humans,Male,Mice Inbred C57BL,Middle Aged,Sequence Analysis DNA,Single-Cell Analysis}
}

@article{zhou2024,
  title = {{{BISCUIT}}: An Efficient, Standards-Compliant Tool Suite for Simultaneous Genetic and Epigenetic Inference in Bulk and Single-Cell Studies},
  shorttitle = {{{BISCUIT}}},
  author = {Zhou, Wanding and Johnson, Benjamin K and Morrison, Jacob and Beddows, Ian and Eapen, James and Katsman, Efrat and Semwal, Ayush and Habib, Walid~Abi and Heo, Lyong and Laird, Peter~W and Berman, Benjamin~P and Triche, Jr., Timothy~J and Shen, Hui},
  year = {2024},
  month = feb,
  journal = {Nucleic Acids Research},
  volume = {52},
  number = {6},
  pages = {gkae097},
  issn = {0305-1048},
  doi = {10.1093/nar/gkae097},
  url = {https://doi.org/10.1093/nar/gkae097},
  urldate = {2024-03-04},
  abstract = {Data from both bulk and single-cell whole-genome DNA methylation experiments are under-utilized in many ways. This is attributable to inefficient mapping of methylation sequencing reads, routinely discarded genetic information, and neglected read-level epigenetic and genetic linkage information. We introduce the BISulfite-seq Command line User Interface Toolkit (BISCUIT) and its companion R/Bioconductor package, biscuiteer, for simultaneous extraction of genetic and epigenetic information from bulk and single-cell DNA methylation sequencing. BISCUIT's performance, flexibility and standards-compliant output allow large, complex experimental designs to be characterized on clinical timescales. BISCUIT is particularly suited for processing data from single-cell DNA methylation assays, with its excellent scalability, efficiency, and ability to greatly enhance mappability, a key challenge for single-cell studies. We also introduce the epiBED format for single-molecule analysis of coupled epigenetic and genetic information, facilitating the study of cellular and tissue heterogeneity from DNA methylation sequencing.},
  copyright = {All rights reserved}
}
