87 research outputs found
ALG: automated genotype calling of Luminex assays.
No full textSingle nucleotide polymorphisms (SNPs) are the most commonly used polymorphic markers in genetics studies. Among the different platforms for SNP genotyping, Luminex is one of the less exploited mainly due to the lack of a robust (semi-automated and replicable) freely available genotype calling software. Here we describe a clustering algorithm that provides automated SNP calls for Luminex genotyping assays. We genotyped 3 SNPs in a cohort of 330 childhood leukemia patients, 200 parents of patient and 325 healthy individuals and used the Automated Luminex Genotyping (ALG) algorithm for SNP calling. ALG genotypes were called twice to test for reproducibility and were compared to sequencing data to test for accuracy. Globally, this analysis demonstrates the accuracy (99.6%) of the method, its reproducibility (99.8%) and the low level of no genotyping calls (3.4%). The high efficiency of the method proves that ALG is a suitable alternative to the current commercial software. ALG is semi-automated, and provides numerical measures of confidence for each SNP called, as well as an effective graphical plot. Moreover ALG can be used either through a graphical user interface, requiring no specific informatics knowledge, or through command line with access to the open source code. The ALG software has been implemented in R and is freely available for non-commercial use either at http://alg.sourceforge.net or by request to [email protected]
Estimation des risques de développer la maladie coeliaque en fonction d'informations génétiques et familiales
No full textLE KREMLIN-B.- PARIS 11-BU Méd (940432101) / SudocPARIS-BIUP (751062107) / SudocSudocFranceF
Modeling the effect of PTPN22 in rheumatoid arthritis.
No full textInternational audienceABSTRACT : In order to model the effect of PTPN22 on rheumatoid arthritis (RA), we determined the combination of single-nucleotide-polymorphisms (SNPs) showing the strongest association with RA. Three SNPs (rs2476601-rs12730735-rs11102685) were selected for which we estimated the genotypic relative risks (GRRs) of the corresponding genotypes. On the basis of these GRRs we defined four at-risk genotypic classes. Relative to the class of reference risk, individuals had a risk approximately multiplied by two, three, or four. This classification was confirmed by the excess of identity-by-descent (IBD) sharing (IBD = 2) for the sibs of an index in the high-risk class and by excess of non-IBD sharing (IBD = 0) when the index belonged to the low-risk class. The observed data could not be explained by the role of a single variant but were compatible either with a joint effect of the three typed SNPs of PTPN22 on RA or with the role of two untyped variants
Power of the 2-locus TDT for testing the interaction of two susceptibility genes.
No full textInternational audienceABSTRACT : We recently proposed a new strategy: 2-locus TDT for detecting two susceptibility genes through their interaction in trio families. We apply our method to two candidate genes, A and C, on the Genetic Analysis Workshop 15 (GAW15) simulated rheumatoid arthritis data and study the power to identify an interactive effect of these genes.This study was performed with full knowledge of the answers
Modeling the effect of PTPN22 in rheumatoid arthritis.
No full textInternational audienceABSTRACT : In order to model the effect of PTPN22 on rheumatoid arthritis (RA), we determined the combination of single-nucleotide-polymorphisms (SNPs) showing the strongest association with RA. Three SNPs (rs2476601-rs12730735-rs11102685) were selected for which we estimated the genotypic relative risks (GRRs) of the corresponding genotypes. On the basis of these GRRs we defined four at-risk genotypic classes. Relative to the class of reference risk, individuals had a risk approximately multiplied by two, three, or four. This classification was confirmed by the excess of identity-by-descent (IBD) sharing (IBD = 2) for the sibs of an index in the high-risk class and by excess of non-IBD sharing (IBD = 0) when the index belonged to the low-risk class. The observed data could not be explained by the role of a single variant but were compatible either with a joint effect of the three typed SNPs of PTPN22 on RA or with the role of two untyped variants
Modeling the effect of PTPN22 in rheumatoid arthritis.
No full textInternational audienceABSTRACT : In order to model the effect of PTPN22 on rheumatoid arthritis (RA), we determined the combination of single-nucleotide-polymorphisms (SNPs) showing the strongest association with RA. Three SNPs (rs2476601-rs12730735-rs11102685) were selected for which we estimated the genotypic relative risks (GRRs) of the corresponding genotypes. On the basis of these GRRs we defined four at-risk genotypic classes. Relative to the class of reference risk, individuals had a risk approximately multiplied by two, three, or four. This classification was confirmed by the excess of identity-by-descent (IBD) sharing (IBD = 2) for the sibs of an index in the high-risk class and by excess of non-IBD sharing (IBD = 0) when the index belonged to the low-risk class. The observed data could not be explained by the role of a single variant but were compatible either with a joint effect of the three typed SNPs of PTPN22 on RA or with the role of two untyped variants
Power of the 2-locus TDT for testing the interaction of two susceptibility genes.
No full textInternational audienceABSTRACT : We recently proposed a new strategy: 2-locus TDT for detecting two susceptibility genes through their interaction in trio families. We apply our method to two candidate genes, A and C, on the Genetic Analysis Workshop 15 (GAW15) simulated rheumatoid arthritis data and study the power to identify an interactive effect of these genes.This study was performed with full knowledge of the answers
Power of the 2-locus TDT for testing the interaction of two susceptibility genes.
No full textInternational audienceABSTRACT : We recently proposed a new strategy: 2-locus TDT for detecting two susceptibility genes through their interaction in trio families. We apply our method to two candidate genes, A and C, on the Genetic Analysis Workshop 15 (GAW15) simulated rheumatoid arthritis data and study the power to identify an interactive effect of these genes.This study was performed with full knowledge of the answers
Modeling the effect of a genetic factor for a complex trait in a simulated population.
No full textGenetic Analysis Workshop 14 simulated data have been analyzed with MASC(marker association segregation chi-squares) in which we implemented a bootstrap procedure to provide the variation intervals of parameter estimates. We model here the effect of a genetic factor, S, for Kofendrerd Personality Disorder in the region of the marker C03R0281 for the Aipotu population. The goodness of fit of several genetic models with two alleles for one locus has been tested. The data are not compatible with a direct effect of a single-nucleotide polymorphism (SNP) (SNP 16, 17, 18, 19 of pack 153) in the region. Therefore, we can conclude that the functional polymorphism has not been typed and is in linkage disequilibrium with the four studied SNPs. We obtained very large variation intervals both of the disease allele frequency and the degree of dominance. The uncertainty of the model parameters can be explained first, by the method used, which models marginal effects when the disease is due to complex interactions, second, by the presence of different sub-criteria used for the diagnosis that are not determined by S in the same way, and third, by the fact that the segregation of the disease in the families was not taken into account. However, we could not find any model that could explain the familial segregation of the trait, namely the higher proportion of affected parents than affected sibs
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