@article{cbsdnacopy,
author = {Olshen, Adam B. and Venkatraman, E. S. and Lucito, Robert and Wigler, Michael}, 
title = {{Circular binary segmentation for the analysis of array-based DNA copy number data}},
volume = {5}, 
number = {4}, 
pages = {557-572}, 
year = {2004}, 
doi = {10.1093/biostatistics/kxh008}, 
abstract ={ DNA sequence copy number is the number of copies of DNA at a region of a genome. Cancer progression often involves alterations in DNA copy number. Newly developed microarray technologies enable simultaneous measurement of copy number at thousands of sites in a genome. We have developed a modification of binary segmentation, which we call circular binary segmentation, to translate noisy intensity measurements into regions of equal copy number. The method is evaluated by simulation and is demonstrated on cell line data with known copy number alterations and on a breast cancer cell line data set. }, 
URL = {http://biostatistics.oxfordjournals.org/content/5/4/557.abstract}, 
eprint = {http://biostatistics.oxfordjournals.org/content/5/4/557.full.pdf+html}, 
journal = {Biostatistics} 
}
@article{variodata,
author = {Schoofs, Till and Rohde, Christian and Hebestreit, Katja and Klein, Hans-Ulrich and Göllner, Stefanie and Schulze, Isabell and Lerdrup, Mads and Dietrich, Nikolaj and Agrawal-Singh, Shuchi and Witten, Anika and Stoll, Monika and Lengfelder, Eva and Hofmann, Wolf-Karsten and Schlenke, Peter and Büchner, Thomas and Hansen, Klaus and Berdel, Wolfgang E. and Rosenbauer, Frank and Dugas, Martin and Müller-Tidow, Carsten}, 
title = {{DNA methylation changes are a late event in acute promyelocytic leukemia and coincide with loss of transcription factor binding}},
volume = {121}, 
number = {1}, 
pages = {178-187}, 
year = {2013}, 
doi = {10.1182/blood-2012-08-448860}, 
abstract ={The origin of aberrant DNA methylation in cancer remains largely unknown. In the present study, we elucidated the DNA methylome in primary acute promyelocytic leukemia (APL) and the role of promyelocytic leukemia–retinoic acid receptor α (PML-RARα) in establishing these patterns. Cells from APL patients showed increased genome-wide DNA methylation with higher variability than healthy CD34+ cells, promyelocytes, and remission BM cells. A core set of differentially methylated regions in APL was identified. Age at diagnosis, Sanz score, and Flt3-mutation status characterized methylation subtypes. Transcription factor–binding sites (eg, the c-myc–binding sites) were associated with low methylation. However, SUZ12- and REST-binding sites identified in embryonic stem cells were preferentially DNA hypermethylated in APL cells. Unexpectedly, PML-RARα–binding sites were also protected from aberrant DNA methylation in APL cells. Consistent with this, myeloid cells from preleukemic PML-RARα knock-in mice did not show altered DNA methylation and the expression of PML-RARα in hematopoietic progenitor cells prevented differentiation without affecting DNA methylation. Treatment of APL blasts with all-trans retinoic acid also did not result in immediate DNA methylation changes. The results of the present study suggest that aberrant DNA methylation is associated with leukemia phenotype but is not required for PML-RARα–mediated initiation of leukemogenesis.}, 
URL = {http://bloodjournal.hematologylibrary.org/content/121/1/178.abstract}, 
eprint = {http://bloodjournal.hematologylibrary.org/content/121/1/178.full.pdf+html}, 
journal = {Blood} 
}
@article{biseq,
author = {Hebestreit, Katja and Dugas, Martin and Klein, Hans-Ulrich}, 
title = {{Detection of Significantly Differentially Methylated Regions in Targeted Bisulfite Sequencing Data}},
year = {2013}, 
doi = {10.1093/bioinformatics/btt263}, 
abstract ={Motivation: Bisulfite sequencing is currently the gold standard to obtain genome-wide DNA methylation profiles in eukaryotes. In contrast to the rapid development of appropriate preprocessing and alignment software, methods for analyzing the resulting methylation profiles are relatively limited so far. For instance, an appropriate pipeline to detect DNA methylation differences between cancer and control samples is still required.Results: We propose an algorithm that detects significantly differentially methylated regions (DMRs) in data obtained by targeted bisulfite sequencing approaches, such as reduced representation bisulfite sequencing (RRBS). In a first step this approach tests all target regions for methylation differences by taking spatial dependence into account. An FDR procedure controls the expected proportion of incorrectly rejected regions. In a second step the significant target regions are trimmed to the actually differentially methylated regions. This hierarchical procedure detects DMRs with increased power compared to existing methods.Availability: R/Bioconductor package BiSeq.Contact: katja.hebestreit@uni-muenster.de}, 
URL = {http://bioinformatics.oxfordjournals.org/content/early/2013/05/08/bioinformatics.btt263.abstract}, 
eprint = {http://bioinformatics.oxfordjournals.org/content/early/2013/05/08/bioinformatics.btt263.full.pdf+html}, 
journal = {Bioinformatics} 
}
@article{snijders2001assembly,
  title={{Assembly of microarrays for genome-wide measurement of DNA copy number}},
  author={Snijders, Antoine M and Nowak, Norma and Segraves, Richard and Blackwood, Stephanie and Brown, Nils and Conroy, Jeffrey and Hamilton, Greg and Hindle, Anna Katherine and Huey, Bing and Kimura, Karen and others},
  journal={Nature genetics},
  volume={29},
  pages={263--264},
  year={2001}
}
@article{ENCODEguide,
    author = {The ENCODE Project Consortium},
    journal = {PLoS Biol},
    publisher = {Public Library of Science},
    title = {{A User's Guide to the Encyclopedia of DNA Elements (ENCODE)}},
    year = {2011},
    month = {04},
    volume = {9},
    url = {http://dx.doi.org/10.1371%2Fjournal.pbio.1001046},
    pages = {e1001046},
    number = {4},
    doi = {10.1371/journal.pbio.1001046}
}
@article{ENCODEproj,
  title={{The ENCODE (ENCyclopedia of DNA elements) project}},
  author={The ENCODE Project Consortium},
  journal={Science},
  volume={306},
  number={5696},
  pages={636--640},
  year={2004}
}
@article{Guedon2003,
    abstract = {{This article addresses the estimation of hidden semi-Markov chains from nonstationary discrete sequences. Hidden semi-Markov chains are particularly useful to model the succession of homogeneous zones or segments along sequences. A discrete hidden semi-Markov chain is composed of a nonobservable state process, which is a semi-Markov chain, and a discrete output process. Hidden semi-Markov chains generalize hidden Markov chains and enable the modeling of various durational structures. From an algorithmic point of view, a new forward-backward algorithm is proposed whose complexity is similar to that of the Viterbi algorithm in terms of sequence length (quadratic in the worst case in time and linear in space). This opens the way to the maximum likelihood estimation of hidden semi-Markov chains from long sequences. This statistical modeling approach is illustrated by the analysis of branching and flowering patterns in plants.}},
    author = {Gu\'{e}don, Yann},
    citeulike-article-id = {4697139},
    citeulike-linkout-0 = {http://dx.doi.org/10.2307/1391041},
    citeulike-linkout-1 = {http://www.jstor.org/stable/1391041},
    doi = {10.2307/1391041},
    issn = {10618600},
    journal = {Journal of Computational and Graphical Statistics},
    keywords = {continuous-time-markov-processes, expectation-maximization, markov-processes},
    number = {3},
    pages = {604--639},
    posted-at = {2009-06-01 05:11:49},
    priority = {2},
    publisher = {American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of America},
    title = {{Estimating Hidden Semi-Markov Chains from Discrete Sequences}},
    url = {http://dx.doi.org/10.2307/1391041},
    volume = {12},
    year = {2003}
} 
@Article{Hubertiling,
author = {Wolfgang Huber and Joern Toedling and Lars M. Steinmetz},
title = {{Transcript mapping with high-density oligonucleotide tiling arrays}},
journal = {Bioinformatics},
year = {2006},
volume = {22},
pages = {1963-1970},
}
﻿@article {mbic2007,
author = {Zhang, Nancy R. and Siegmund, David O.},
title = {{A Modified Bayes Information Criterion with Applications to the Analysis of Comparative Genomic Hybridization Data}},
journal = {Biometrics},
volume = {63},
number = {1},
publisher = {Blackwell Publishing Inc},
issn = {1541-0420},
url = {http://dx.doi.org/10.1111/j.1541-0420.2006.00662.x},
doi = {10.1111/j.1541-0420.2006.00662.x},
pages = {22--32},
keywords = {Bayes information criterion, Change-point, Comparative genomic hybridization, Model selection},
year = {2007},
}
@Article{biomvrcns2013fbn,
AUTHOR = {Du, Yang and Murani, Eduard and Ponsuksili, Siriluck and Wimmers, Klaus},
TITLE = {{biomvRhsmm: Genomic segmentation with hidden semi-Markov model}},
JOURNAL = {{BioMed Research International}},
DOI = {10.1155/2014/910390},
VOLUME = {2014},
YEAR = {2014},
ISSN = {2314-6133}
}
