Relational analysis of CpG islands methylation and gene expression in human lymphomas using possibilistic C-means clustering and modified cluster fuzzy density.
Heterogeneous genetic and epigenetic alterations are commonly found in human non-Hodgkin's lymphomas (NHL). One such epigenetic alteration is aberrant methylation of gene promoter-related CpG islands, where hypermethylation frequently results in transcriptional inactivation of target genes, while a decrease or loss of promoter methylation (hypomethylation) is frequently associated with transcriptional activation. Discovering genes with these relationships in NHL or other types of cancers could lead to a better understanding of the pathobiology of these diseases. The simultaneous analysis of promoter methylation using Differential Methylation Hybridization (DMH) and its associated gene expression using Expressed CpG Island Sequence Tag (ECIST) microarrays generates a large volume of methylation-expression relational data. To analyze this data, we propose a set of algorithms based on fuzzy sets theory, in particular Possibilistic c-Means (PCM) and cluster fuzzy density. For each gene, these algorithms calculate measures of confidence of various methylation-expression relationships in each NHL subclass. Thus, these tools can be used as a means of high volume data exploration to better guide biological confirmation using independent molecular biology methods.
Sjahputera
Ozy
O
Ellis Fischel Cancer Research Lab, Department of Pathology and Anatomical Sciences, University of Missouri School of Medicine, Columbia, MO 65212, USA. sjahputerao@missouri.edu
Keller
James M
JM
Davis
J Wade
JW
Taylor
Kristen H
KH
Rahmatpanah
Farahnaz
F
Shi
Huidong
H
Anderson
Derek T
DT
Blisard
Samuel N
SN
Luke
Robert H
RH
Popescu
Mihail
M
Arthur
Gerald C
GC
Caldwell
Charles W
CW
D001185:Artificial Intelligence; D014408:Biomarkers, Tumor / Q000235:genetics*; D016000:Cluster Analysis; D003198:Computer Simulation; D018899:CpG Islands / Q000235:genetics*; D019175:DNA Methylation; D003627:Data Interpretation, Statistical; D017143:Fuzzy Logic; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008228:Lymphoma, Non-Hodgkin / Q000235:genetics*; D008957:Models, Genetic; D015233:Models, Statistical; D009363:Neoplasm Proteins / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D013223:Statistics as Topic
D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins