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MLR-Tagging Package : Genotype Tagging Based on Multivariate Linear Regression version 1.1 MLR-Tagging software package implements a novel genotype tagging method based on multivariate linear regression (MLR) analysis. This software can be used for tag selection and genotype prediction. The stepwise tag selection algorithm (STA) selects positions of the given number of tags based on a genotype sample population. The MLR SNP prediction algorithm predicts a complete genotype based on the values of its tag SNPs, tag positions among all SNPs, and a sample of complete genotypes. An extensive experimental study on various datasets including 10 regions from HapMap shows that the MLR prediction combined with stepwise tag selection uses fewer tags than the state-of-the-art method of STAMPA. Manual: taggingReadme.pdf Please cite the related articles if you use them in your research: Or send an e-mail to alexz@cs.gsu.edu and cc jingwu@cs.gsu.edu which includes:subject: Request for MLR-Tagging Package body: 1. Name. 2. Affiliation. 3. Maximum datasize (# of genotypes in your data / # of SNPs in your data)
Contacts: 34
Peachtree Street, Suite 1443 web:http://www.cs.gsu.edu/~cscazz/ Jingwu Jim He Phone: (404) 463-2808 Email: jingwu@cs.gsu.edu Department of Computer Science Georgia State University 34
Peachtree Street, Suite 1415 web:http://www.cs.gsu.edu/~cscjghx/
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