% IMPORTANT: The following is UTF-8 encoded. This means that in the presence % of non-ASCII characters, it will not work with BibTeX 0.99 or older. % Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or % “biber”. @ARTICLE{Slynko:144015, author = {A. Slynko and A. Benner$^*$}, title = {{S}tatistical methods for classification of 5hm{C} levels based on the {I}llumina {I}nifinium {H}uman{M}ethylation450 (450k) array data, under the paired bisulfite ({BS}) and oxidative bisulfite (ox{BS}) treatment.}, journal = {PLOS ONE}, volume = {14}, number = {6}, issn = {1932-6203}, address = {San Francisco, California, US}, publisher = {PLOS}, reportid = {DKFZ-2019-01566}, pages = {e0218103 -}, year = {2019}, abstract = {Hydroxymethylcytosine (5hmC) methylation is a well-known epigenetic mark that is involved in gene regulation and may impact genome stability. To investigate a possible role of 5hmC in cancer development and progression, one must be able to detect and quantify its level first. In this paper, we address the issue of 5hmC detection at a single base resolution, starting with consideration of the well-established 5hmC measure Δβ and, in particular, with an analysis of its properties, both analytically and empirically. Then we propose several alternative hydroxymethylation measures and compare their properties with those of Δβ. In the absence of a gold standard, the (pairwise) resemblance of those 5hmC measures to Δβ is characterized by means of a similarity analysis and relative accuracy analysis. All results are illustrated on matched healthy and cancer tissue data sets as derived by means of bisulfite (BS) and oxidative bisulfite converting (oxBS) procedures.}, cin = {C060}, ddc = {610}, cid = {I:(DE-He78)C060-20160331}, pnm = {313 - Cancer risk factors and prevention (POF3-313)}, pid = {G:(DE-HGF)POF3-313}, typ = {PUB:(DE-HGF)16}, pubmed = {pmid:31194780}, doi = {10.1371/journal.pone.0218103}, url = {https://inrepo02.dkfz.de/record/144015}, }