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An analytical pipeline for genomic representations used for cytosine methylation studies
Author(s) -
Reid F. Thompson,
Mark Reimers,
Batbayar Khulan,
Mathieu Gissot,
Todd Richmond,
Quan Chen,
Xin Zheng,
Kami Kim,
John M. Greally
Publication year - 2008
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btn096
Subject(s) - pipeline (software) , dna methylation , computer science , cytosine , computational biology , methylation , genetics , biology , programming language , dna , gene , gene expression
Representations of the genome can be generated by the selection of a subpopulation of restriction fragments using ligation-mediated PCR. Such representations form the basis for a number of high-throughput assays, including the HELP assay to study cytosine methylation. We find that HELP data analysis is complicated not only by PCR amplification heterogeneity but also by a complex and variable distribution of cytosine methylation. To address this, we created an analytical pipeline and novel normalization approach that improves concordance between microarray-derived data and single locus validation results, demonstrating the value of the analytical approach. A major influence on the PCR amplification is the size of the restriction fragment, requiring a quantile normalization approach that reduces the influence of fragment length on signal intensity. Here we describe all of the components of the pipeline, which can also be applied to data derived from other assays based on genomic representations.

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