Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.
Department of Preventive Medicine, Department of Biomedical Informatics, and Department of Applied Mathematics and Statistics, Stony Brook University, Stony Brook, NY 11794, Department of Biostatistics, Yale University, New Haven, CT 06520, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, Department of Pathology, Stony Brook University, Stony Brook, NY 11794, Department of Medicine, Washington University St Louis, St Louis, MO 63110 and Department of Medicine, Stony Brook University, Stony Brook, NY 11794, USA.
Bioinformatics. 2015 Jun 15;31(12):2040-2. doi: 10.1093/bioinformatics/btv089. Epub 2015 Feb 13.
Currently available bisulfite sequencing tools frequently suffer from low mapping rates and low methylation calls, especially for data generated from the Illumina sequencer, NextSeq. Here, we introduce a sequential trimming-and-retrieving alignment approach for investigating DNA methylation patterns, which significantly improves the number of mapped reads and covered CpG sites. The method is implemented in an automated analysis toolkit for processing bisulfite sequencing reads.
http://mysbfiles.stonybrook.edu/~xuefenwang/software.html and https://github.com/xfwang/BStools.
目前可用的亚硫酸氢盐测序工具经常存在低映射率和低甲基化调用的问题,特别是对于 Illumina 测序仪 NextSeq 生成的数据。在这里,我们引入了一种用于研究 DNA 甲基化模式的顺序修剪和检索对齐方法,该方法显著提高了映射读取和覆盖的 CpG 位点的数量。该方法在一个用于处理亚硫酸氢盐测序读取的自动分析工具包中实现。
http://mysbfiles.stonybrook.edu/~xuefenwang/software.html 和 https://github.com/xfwang/BStools。