DocumentCode :
472222
Title :
Cancer Classification Using Loss of Heterozygosity Data Derived from Single-Nucleotide Polymorphism Genotyping Arrays
Author :
Wang, Yuhang
Author_Institution :
Dept. of Comput. Sci. & Eng., Southern Methodist Univ., Dallas, TX
fYear :
2006
fDate :
Aug. 30 2006-Sept. 3 2006
Firstpage :
5864
Lastpage :
5867
Abstract :
Single-Nucleotide Polymorphism (SNP) array is a recently introduced technology that genotypes more than 10,000 human SNPs on a single array. It has been shown that genome-wide Loss of Heterozygosity (LOH) calls can be derived by analyzing the genotypes calls measured by SNP arrays using paired tumor and normal tissue samples. The goal of this study is to evaluate the possibility of cancer classification using LOH calls. As a proof of concept, we applied 16 different combinations of classification algorithms and feature selection algorithms to a public data set that contains LOH calls of 10,043 SNP loci obtained from 10 breast cancer patients and 5 small cell lung cancer (SCLC) patients. Performance was measured in terms of the leave-one-out cross-validation (LOOCV) classification accuracy. Experimental results suggest that LOH calls derived from SNP arrays can be an excellent indicator of cancer type
Keywords :
cancer; cellular biophysics; genetics; gynaecology; learning (artificial intelligence); medical computing; molecular biophysics; pattern classification; polymorphism; support vector machines; tumours; breast cancer classification; feature selection algorithm; genome; genotype analysis; human single-nucleotide polymorphism genotyping arrays; leave-one-out cross-validation classification accuracy; loss-of-heterozygosity data; machine learning; normal tissue samples; paired tumor; public data set; small cell lung cancer patient; support vector machine; Bioinformatics; Cancer; Classification algorithms; Gene expression; Genomics; Humans; Loss measurement; Machine learning; Machine learning algorithms; Neoplasms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
Conference_Location :
New York, NY
ISSN :
1557-170X
Print_ISBN :
1-4244-0032-5
Electronic_ISBN :
1557-170X
Type :
conf
DOI :
10.1109/IEMBS.2006.260116
Filename :
4463141
Link To Document :
بازگشت