The Experts below are selected from a list of 8463 Experts worldwide ranked by ideXlab platform

Carmen Arnal - One of the best experts on this subject based on the ideXlab platform.

  • Tag-SNP analysis of the GFI1-EVI5-RPL5-FAM69 risk locus for multiple sclerosis
    European Journal of Human Genetics, 2010
    Co-Authors: Fuencisla Matesanz, Antonio Alcina, Oscar Fernández, Juan R González, Antonio Catalá-rabasa, Maria Fedetz, Dorothy Ndagire, Laura Leyva, Miguel Guerrero, Carmen Arnal
    Abstract:

    A recent genome-wide association study conducted by the International Multiple Sclerosis Genetic Consortium (IMSGC) identified, among others, a number of putative multiple sclerosis (MS) susceptibility variants at position 1p22. Twenty one SNPs positively associated with MS were located at the GFI -EVI5-RPL5-FAM69A locus. In this study, we performed an analysis and fine mapping of this locus genotyping 8 Tag-SNPs up to 732 MS patients and 974 controls from Spain. We observed association with MS in 3 of 8 Tag-SNPs: rs11804321 (P=0.008. OR=1.29; 95% CI=1.08-1.54), rs11808092 (P=0.048. OR=1.19; 95% CI=1.03-1.39) and rs6680578 (P=0.0082. OR=1.23; 95% CI=1.07-1.41). After correcting for multiple comparisons and using logistic regression analysis to test the addition of each SNP to the most associated SNPs, we observed that the rs11804321 alone was sufficient to model the association. This Tag-SNP captures two SNPs in complete linkage disequilibrium (r2 = 1) both located within the 17th intron of EVI5 gene. Our findings agree with the corresponding data of the recent IMSGC study and present new genetic evidence that point to EVI5 as a factor of susceptibility to MS.

  • Tag SNP analysis of the gfi1 evi5 rpl5 fam69 risk locus for multiple sclerosis
    European Journal of Human Genetics, 2010
    Co-Authors: Antonio Alcina, Oscar Fernández, Juan R González, Maria Fedetz, Dorothy Ndagire, Laura Leyva, Carmen Arnal, Antonio Catalarabasa, Miguel G Guerrero, Concepcion Delgado
    Abstract:

    A recent genome-wide association study conducted by the International Multiple Sclerosis Genetic Consortium (IMSGC) identified, among others, a number of putative multiple sclerosis (MS) susceptibility variants at position 1p22. Twenty-one SNPs positively associated with MS were located at the GFI-EVI5-RPL5-FAM69A locus. In this study, we performed an analysis and fine mapping of this locus, genotyping eight Tag-SNPs in 732 MS patients and 974 controls from Spain. We observed an association with MS in three of eight Tag-SNPs: rs11804321 (P=0.008, OR=1.29; 95% CI=1.08–1.54), rs11808092 (P=0.048, OR=1.19; 95% CI=1.03–1.39) and rs6680578 (P=0.0082, OR=1.23; 95% CI=1.07–1.41). After correcting for multiple comparisons and using logistic regression analysis to test the addition of each SNP to the most associated SNPs, we observed that rs11804321 alone was sufficient to model the association. This Tag-SNP captures two SNPs in complete linkage disequilibrium (r2=1), both located within the 17th intron of the EVI5 gene. Our findings agree with the corresponding data of the recent IMSGC study and present new genetic evidence that points to EVI5 as a factor of susceptibility to MS.

Antonio Alcina - One of the best experts on this subject based on the ideXlab platform.

  • Tag-SNP analysis of the GFI1-EVI5-RPL5-FAM69 risk locus for multiple sclerosis
    European Journal of Human Genetics, 2010
    Co-Authors: Fuencisla Matesanz, Antonio Alcina, Oscar Fernández, Juan R González, Antonio Catalá-rabasa, Maria Fedetz, Dorothy Ndagire, Laura Leyva, Miguel Guerrero, Carmen Arnal
    Abstract:

    A recent genome-wide association study conducted by the International Multiple Sclerosis Genetic Consortium (IMSGC) identified, among others, a number of putative multiple sclerosis (MS) susceptibility variants at position 1p22. Twenty one SNPs positively associated with MS were located at the GFI -EVI5-RPL5-FAM69A locus. In this study, we performed an analysis and fine mapping of this locus genotyping 8 Tag-SNPs up to 732 MS patients and 974 controls from Spain. We observed association with MS in 3 of 8 Tag-SNPs: rs11804321 (P=0.008. OR=1.29; 95% CI=1.08-1.54), rs11808092 (P=0.048. OR=1.19; 95% CI=1.03-1.39) and rs6680578 (P=0.0082. OR=1.23; 95% CI=1.07-1.41). After correcting for multiple comparisons and using logistic regression analysis to test the addition of each SNP to the most associated SNPs, we observed that the rs11804321 alone was sufficient to model the association. This Tag-SNP captures two SNPs in complete linkage disequilibrium (r2 = 1) both located within the 17th intron of EVI5 gene. Our findings agree with the corresponding data of the recent IMSGC study and present new genetic evidence that point to EVI5 as a factor of susceptibility to MS.

  • Tag SNP analysis of the gfi1 evi5 rpl5 fam69 risk locus for multiple sclerosis
    European Journal of Human Genetics, 2010
    Co-Authors: Antonio Alcina, Oscar Fernández, Juan R González, Maria Fedetz, Dorothy Ndagire, Laura Leyva, Carmen Arnal, Antonio Catalarabasa, Miguel G Guerrero, Concepcion Delgado
    Abstract:

    A recent genome-wide association study conducted by the International Multiple Sclerosis Genetic Consortium (IMSGC) identified, among others, a number of putative multiple sclerosis (MS) susceptibility variants at position 1p22. Twenty-one SNPs positively associated with MS were located at the GFI-EVI5-RPL5-FAM69A locus. In this study, we performed an analysis and fine mapping of this locus, genotyping eight Tag-SNPs in 732 MS patients and 974 controls from Spain. We observed an association with MS in three of eight Tag-SNPs: rs11804321 (P=0.008, OR=1.29; 95% CI=1.08–1.54), rs11808092 (P=0.048, OR=1.19; 95% CI=1.03–1.39) and rs6680578 (P=0.0082, OR=1.23; 95% CI=1.07–1.41). After correcting for multiple comparisons and using logistic regression analysis to test the addition of each SNP to the most associated SNPs, we observed that rs11804321 alone was sufficient to model the association. This Tag-SNP captures two SNPs in complete linkage disequilibrium (r2=1), both located within the 17th intron of the EVI5 gene. Our findings agree with the corresponding data of the recent IMSGC study and present new genetic evidence that points to EVI5 as a factor of susceptibility to MS.

Cheng-hong Yang - One of the best experts on this subject based on the ideXlab platform.

  • Tag SNP selection using particle swarm optimization.
    Biotechnology progress, 2010
    Co-Authors: Li-yeh Chuang, Cheng-san Yang, Cheng-hong Yang
    Abstract:

    Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variations amongst species. With the genome-wide SNP discovery, many genome-wide association studies are likely to identify multiple genetic variants that are associated with complex diseases. However, genotyping all existing SNPs for a large number of samples is still challenging even though SNP arrays have been developed to facilitate the task. Therefore, it is essential to select only informative SNPs representing the original SNP distributions in the genome (Tag SNP selection) for genome-wide association studies. These SNPs are usually chosen from haplotypes and called haplotype Tag SNPs (htSNPs). Accordingly, the scale and cost of genotyping are expected to be largely reduced. We introduce binary particle swarm optimization (BPSO) with local search capability to improve the prediction accuracy of STAMPA. The proposed method does not rely on block partitioning of the genomic region, and consistently identified Tag SNPs with higher prediction accuracy than either STAMPA or SVM/STSA. We compared the prediction accuracy and time complexity of BPSO to STAMPA and an SVM-based (SVM/STSA) method using publicly available data sets. For STAMPA and SVM/STSA, BPSO effective improved prediction accuracy for smaller and larger scale data sets. These results demonstrate that the BPSO method selects Tag SNP with higher accuracy no matter the scale of data sets is used.

  • fuzzy guided bpso method for haplotype Tag SNP selection
    IEEE International Conference on Fuzzy Systems, 2009
    Co-Authors: Li-yeh Chuang, Yujen Hou, Cheng-hong Yang
    Abstract:

    In the current researches of disease-gene association, Single Nucleotide Polymorphism (SNP) is the most interested topic. However, genotyping all existing SNPs for a large number of samples is still challenging even though SNP arrays have been developed to facilitate the task. Therefore, it is essential to select only informative SNPs (Tag SNP) representing the rest SNPs for genome-wide association studies. Accordingly, the cost of genotyping is expected to be largely reduced. In this study, the fuzzy guided binary particle swarm optimization (FBPSO) based approach make it possible to select Tag SNPs with higher accuracy. The fuzzy logic is employed to tuning the inertia weight (w) of BPSO. Three publicly data sets from the literature have been used for testing the performance of FBPSO. The experimental results indicated that the fuzzy logic will reinforce the search capability of BPSO, which is more accurate than the state-of-the-art methods. On the average of testing results, it also outperforms SVM/STSA method about 3.7%.

  • FUZZ-IEEE - Fuzzy guided BPSO method for haplotype Tag SNP selection
    2009 IEEE International Conference on Fuzzy Systems, 2009
    Co-Authors: Li-yeh Chuang, Yujen Hou, Cheng-hong Yang
    Abstract:

    In the current researches of disease-gene association, Single Nucleotide Polymorphism (SNP) is the most interested topic. However, genotyping all existing SNPs for a large number of samples is still challenging even though SNP arrays have been developed to facilitate the task. Therefore, it is essential to select only informative SNPs (Tag SNP) representing the rest SNPs for genome-wide association studies. Accordingly, the cost of genotyping is expected to be largely reduced. In this study, the fuzzy guided binary particle swarm optimization (FBPSO) based approach make it possible to select Tag SNPs with higher accuracy. The fuzzy logic is employed to tuning the inertia weight (w) of BPSO. Three publicly data sets from the literature have been used for testing the performance of FBPSO. The experimental results indicated that the fuzzy logic will reinforce the search capability of BPSO, which is more accurate than the state-of-the-art methods. On the average of testing results, it also outperforms SVM/STSA method about 3.7%.

  • improved Tag SNP selection using binary particle swarm optimization
    World Congress on Computational Intelligence, 2008
    Co-Authors: Cheng-hong Yang, Li-yeh Chuang
    Abstract:

    Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, they are limited by the cost of genotyping the tremendous number of SNPs. It is therefore essential to select only informative subsets (Tag SNPs) out of all SNPs. Several promising methods for Tag SNP selection have been proposed, such as the haplotype block-based and block-free approaches. The block-free methods are preferred by some researchers because most of the block-based methods rely on strong assumptions, such as prior block-partitioning, bi-allelic SNPs, or a fixed number or locations for Tagging SNPs. We employed the feature selection idea of binary particle swarm optimization (binary PSO) to find informative Tag SNPs. This method is very efficient, as it does not rely on block partitioning of the genomic region. Using four public data sets, the method consistently identified Tag SNPs with considerably better prediction ability than STAMPA. Moreover, this method retains its performance even when a very small number and 100% prediction accuracy are used for the Tag SNPs.

  • IEEE Congress on Evolutionary Computation - Improved Tag SNP selection using binary particle swarm optimization
    2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 2008
    Co-Authors: Cheng-hong Yang, Li-yeh Chuang
    Abstract:

    Single nucleotide polymorphisms (SNPs) hold much promise as a basis for disease-gene association. However, they are limited by the cost of genotyping the tremendous number of SNPs. It is therefore essential to select only informative subsets (Tag SNPs) out of all SNPs. Several promising methods for Tag SNP selection have been proposed, such as the haplotype block-based and block-free approaches. The block-free methods are preferred by some researchers because most of the block-based methods rely on strong assumptions, such as prior block-partitioning, bi-allelic SNPs, or a fixed number or locations for Tagging SNPs. We employed the feature selection idea of binary particle swarm optimization (binary PSO) to find informative Tag SNPs. This method is very efficient, as it does not rely on block partitioning of the genomic region. Using four public data sets, the method consistently identified Tag SNPs with considerably better prediction ability than STAMPA. Moreover, this method retains its performance even when a very small number and 100% prediction accuracy are used for the Tag SNPs.

Concepcion Delgado - One of the best experts on this subject based on the ideXlab platform.

  • Tag SNP analysis of the gfi1 evi5 rpl5 fam69 risk locus for multiple sclerosis
    European Journal of Human Genetics, 2010
    Co-Authors: Antonio Alcina, Oscar Fernández, Juan R González, Maria Fedetz, Dorothy Ndagire, Laura Leyva, Carmen Arnal, Antonio Catalarabasa, Miguel G Guerrero, Concepcion Delgado
    Abstract:

    A recent genome-wide association study conducted by the International Multiple Sclerosis Genetic Consortium (IMSGC) identified, among others, a number of putative multiple sclerosis (MS) susceptibility variants at position 1p22. Twenty-one SNPs positively associated with MS were located at the GFI-EVI5-RPL5-FAM69A locus. In this study, we performed an analysis and fine mapping of this locus, genotyping eight Tag-SNPs in 732 MS patients and 974 controls from Spain. We observed an association with MS in three of eight Tag-SNPs: rs11804321 (P=0.008, OR=1.29; 95% CI=1.08–1.54), rs11808092 (P=0.048, OR=1.19; 95% CI=1.03–1.39) and rs6680578 (P=0.0082, OR=1.23; 95% CI=1.07–1.41). After correcting for multiple comparisons and using logistic regression analysis to test the addition of each SNP to the most associated SNPs, we observed that rs11804321 alone was sufficient to model the association. This Tag-SNP captures two SNPs in complete linkage disequilibrium (r2=1), both located within the 17th intron of the EVI5 gene. Our findings agree with the corresponding data of the recent IMSGC study and present new genetic evidence that points to EVI5 as a factor of susceptibility to MS.

Oscar Fernández - One of the best experts on this subject based on the ideXlab platform.

  • Tag-SNP analysis of the GFI1-EVI5-RPL5-FAM69 risk locus for multiple sclerosis
    European Journal of Human Genetics, 2010
    Co-Authors: Fuencisla Matesanz, Antonio Alcina, Oscar Fernández, Juan R González, Antonio Catalá-rabasa, Maria Fedetz, Dorothy Ndagire, Laura Leyva, Miguel Guerrero, Carmen Arnal
    Abstract:

    A recent genome-wide association study conducted by the International Multiple Sclerosis Genetic Consortium (IMSGC) identified, among others, a number of putative multiple sclerosis (MS) susceptibility variants at position 1p22. Twenty one SNPs positively associated with MS were located at the GFI -EVI5-RPL5-FAM69A locus. In this study, we performed an analysis and fine mapping of this locus genotyping 8 Tag-SNPs up to 732 MS patients and 974 controls from Spain. We observed association with MS in 3 of 8 Tag-SNPs: rs11804321 (P=0.008. OR=1.29; 95% CI=1.08-1.54), rs11808092 (P=0.048. OR=1.19; 95% CI=1.03-1.39) and rs6680578 (P=0.0082. OR=1.23; 95% CI=1.07-1.41). After correcting for multiple comparisons and using logistic regression analysis to test the addition of each SNP to the most associated SNPs, we observed that the rs11804321 alone was sufficient to model the association. This Tag-SNP captures two SNPs in complete linkage disequilibrium (r2 = 1) both located within the 17th intron of EVI5 gene. Our findings agree with the corresponding data of the recent IMSGC study and present new genetic evidence that point to EVI5 as a factor of susceptibility to MS.

  • Tag SNP analysis of the gfi1 evi5 rpl5 fam69 risk locus for multiple sclerosis
    European Journal of Human Genetics, 2010
    Co-Authors: Antonio Alcina, Oscar Fernández, Juan R González, Maria Fedetz, Dorothy Ndagire, Laura Leyva, Carmen Arnal, Antonio Catalarabasa, Miguel G Guerrero, Concepcion Delgado
    Abstract:

    A recent genome-wide association study conducted by the International Multiple Sclerosis Genetic Consortium (IMSGC) identified, among others, a number of putative multiple sclerosis (MS) susceptibility variants at position 1p22. Twenty-one SNPs positively associated with MS were located at the GFI-EVI5-RPL5-FAM69A locus. In this study, we performed an analysis and fine mapping of this locus, genotyping eight Tag-SNPs in 732 MS patients and 974 controls from Spain. We observed an association with MS in three of eight Tag-SNPs: rs11804321 (P=0.008, OR=1.29; 95% CI=1.08–1.54), rs11808092 (P=0.048, OR=1.19; 95% CI=1.03–1.39) and rs6680578 (P=0.0082, OR=1.23; 95% CI=1.07–1.41). After correcting for multiple comparisons and using logistic regression analysis to test the addition of each SNP to the most associated SNPs, we observed that rs11804321 alone was sufficient to model the association. This Tag-SNP captures two SNPs in complete linkage disequilibrium (r2=1), both located within the 17th intron of the EVI5 gene. Our findings agree with the corresponding data of the recent IMSGC study and present new genetic evidence that points to EVI5 as a factor of susceptibility to MS.