@inbook{47bc2ad171a1483b800f7dad50a58fa1,
title = "Automated computational analysis of genome-wide DNA methylation profiling data from HELP-tagging assays",
abstract = "A novel DNA methylation assay, HELP-tagging, has been recently described to use massively parallel sequencing technology for genome-wide methylation profiling. Massively parallel sequencing-based assays such as this produce substantial amounts of data, which complicate analysis and necessitate the use of significant computational resources. To simplify the processing and analysis of HELP-tagging data, a bioinformatic analytical pipeline was developed. Quality checks are performed on the data at various stages, as they are processed by the pipeline to ensure the accuracy of the results. A quantitative methylation score is provided for each locus, along with a confidence score based on the amount of information available for determining the quantification. HELP-tagging analysis results are supplied in standard file formats (BED and WIG) that can be readily examined on the UCSC genome browser.",
keywords = "Bioinformatics, Computational analysis, DNA methylation, Pipeline",
author = "Qiang Jing and Andrew McLellan and Greally, {John M.} and Masako Suzuki",
year = "2012",
doi = "10.1007/978-1-61779-424-7_7",
language = "English (US)",
isbn = "9781617794230",
series = "Methods in Molecular Biology",
pages = "79--87",
editor = "Michael Kaufmann and Claudia Klinger",
booktitle = "Functional Genomics",
}