TY - JOUR
T1 - Identifying differentially methylated regions by efficient bit-masking of DNA microarrays to use as markers for non invasive prenatal diagnosis
AU - Antoniou, Pavlos
AU - Michalakopoulos, Spiros
AU - Ioannides, Marios
AU - Papageorgiou, Elisavet A.
AU - Patsalis, Philippos C.
N1 - Publisher Copyright:
© 2014 CRL Publishing Ltd.
PY - 2014/6/1
Y1 - 2014/6/1
N2 - Differentially methylated regions (DMRs) are segments or islands of consecutive sequence positions, showing methylation enrichment or depletion compared to each other in different samples or tissues. The identification of DMRs is a crucial first step in the discovery of biomarkers for non-invasive prenatal diagnosis of aneuploidies such as Trisomy 21. In this paper we describe an algorithm to automatically identify the manifestation of DMRs on arrays. Our approach, methylation status mask AND (MS-AND), influenced by the SHIFT-AND methodology, uses bit operations and masking and can be applied to any microarray dataset in General Feature Format (GFF). We show the effectiveness and utilization of our algorithm using data from Methylated DNA Immunoprecipitation arrays for the identification of DMRs in chromosomes 13, 18 and 21. The algorithm runs on Linux and on Windows systems and an implementation is available at sourceforge (http://sourceforge.net/projects/ms-and). This paper is a revised and extended version of Antoniou et al. [1], presented at BIBE 2013.
AB - Differentially methylated regions (DMRs) are segments or islands of consecutive sequence positions, showing methylation enrichment or depletion compared to each other in different samples or tissues. The identification of DMRs is a crucial first step in the discovery of biomarkers for non-invasive prenatal diagnosis of aneuploidies such as Trisomy 21. In this paper we describe an algorithm to automatically identify the manifestation of DMRs on arrays. Our approach, methylation status mask AND (MS-AND), influenced by the SHIFT-AND methodology, uses bit operations and masking and can be applied to any microarray dataset in General Feature Format (GFF). We show the effectiveness and utilization of our algorithm using data from Methylated DNA Immunoprecipitation arrays for the identification of DMRs in chromosomes 13, 18 and 21. The algorithm runs on Linux and on Windows systems and an implementation is available at sourceforge (http://sourceforge.net/projects/ms-and). This paper is a revised and extended version of Antoniou et al. [1], presented at BIBE 2013.
UR - https://www.scopus.com/pages/publications/84923540108
M3 - Article
AN - SCOPUS:84923540108
SN - 1472-8915
VL - 22
SP - 109
EP - 117
JO - Engineering Intelligent Systems
JF - Engineering Intelligent Systems
IS - 2
ER -