TY - GEN
T1 - Automated selection of differentially methylated regions in microarray data
AU - Antoniou, Pavlos
AU - Michalakopoulos, Spiros
AU - Papageorgiou, Elisavet A.
AU - Patsalis, Philippos C.
AU - Sismani, Carolina
PY - 2013
Y1 - 2013
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 noninvasive 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).
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 noninvasive 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).
UR - https://www.scopus.com/pages/publications/84894209731
U2 - 10.1109/BIBE.2013.6701643
DO - 10.1109/BIBE.2013.6701643
M3 - Conference contribution
AN - SCOPUS:84894209731
SN - 9781479931637
T3 - 13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013
BT - 13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013
T2 - 13th IEEE International Conference on BioInformatics and BioEngineering, IEEE BIBE 2013
Y2 - 10 November 2013 through 13 November 2013
ER -