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Le Touquet – Paris-Plage, France

Genin E.,University Paris Diderot | Genin E.,French Institute of Health and Medical Research | Sahbatou M.,Fondation Jean Dausset CEPH | Gazal S.,University Paris Diderot | And 4 more authors.
Human Heredity | Year: 2012

To detect fully penetrant rare recessive variants that could constitute Mendelian subentities of complex diseases, we propose a novel strategy, the HBD-GWAS strategy, which can be applied to genome-wide association study (GWAS) data. This strategy first involves the identification of inbred individuals among cases using the genome-wide SNP data and then focuses on these inbred affected individuals and searches for genomic regions of shared homozygosity by descent that could harbor rare recessive disease-causing variants. In this second step, analogous to homozygosity mapping, a heterogeneity lod-score, HFLOD, is computed to quantify the evidence of linkage provided by the data. In this paper, we evaluate this strategy theoretically under different scenarios and compare its performances with those of linkage analysis using affected sib-pair (ASP) data. If cases affected by these Mendelian subentities are not enriched in the sample of cases, the HBD-GWAS strategy has almost no power to detect them, unless they explain an important part of the disease prevalence. The HBD-GWAS strategy outperforms the ASP linkage strategy only in a very limited number of situations where there exists a strong allelic heterogeneity. When several rare recessive variants within the same gene are involved, the ASP design indeed often fails to detect the gene, whereas, by focusing on inbred individuals using the HBD-GWAS strategy, the gene might be detected provided very large samples of cases are available. Copyright © 2013 S. Karger AG, Basel. Source


Babron M.-C.,French Institute of Health and Medical Research | Babron M.-C.,University Paris Diderot | Guilloud-Bataille M.,French Institute of Health and Medical Research | Guilloud-Bataille M.,University Paris - Sud | And 7 more authors.
Genetic Epidemiology | Year: 2012

Not accounting for interaction in association analyses may reduce the power to detect the variants involved. We investigate the powers of different designs to detect under two-locus models the effect of disease-causing variants among several hundreds of markers using family-based association tests by simulation. This setting reflects realistic situations of exploration of linkage regions or of biological pathways. We define four strategies: (S1) single-marker analysis of all Single Nucleotide Polymorphisms (SNPs), (S2) two-marker analysis of all possible SNPs pairs, (S3) lax preliminary selection of SNPs followed by a two-marker analysis of all selected SNP pairs, (S4) stringent preliminary selection of SNPs, each being later paired with all the SNPs for two-marker analysis. Strategy S2 is never the best design, except when there is an inversion of the gene effect (flip-flop model). Testing individual SNPs (S1) is the most efficient when the two genes act multiplicatively. Designs S3 and S4 are the most powerful for nonmultiplicative models. Their respective powers depend on the level of symmetry of the model. Because the true genetic model is unknown, we cannot conclude that one design outperforms another. The optimal approach would be the two-step strategy (S3 or S4) as it is often the most powerful, or the second best. Genet. © 2012 Wiley Periodicals, Inc. Source


Jalkh N.,Saint - Joseph University | Jalkh N.,University of Versailles | Sahbatou M.,Fondation Jean Dausset CEPH | Chouery E.,Saint - Joseph University | And 4 more authors.
European Journal of Human Genetics | Year: 2015

Consanguineous marriages have been widely practiced in several global communities with varying rates depending on religion, culture, and geography. In consanguineous marriages, parents pass to their children autozygous segments known as homozygous by descent segments. In this study, single-nucleotide polymorphisms were analyzed in 165 unrelated Lebanese people from Greek Orthodox, Maronite, Shiite and Sunni communities. Runs of homozygosity, total inbreeding levels, remote consanguinity, and population admixture and structure were estimated. The inbreeding coefficient value was estimated to be 1.61% in offspring of unrelated parents over three generations and 8.33% in offspring of first cousins. From these values, remote consanguinity values, resulting from genetic drift or recurrent consanguineous unions, were estimated in offspring of unrelated and first-cousin parents to be 0.61 and 1.2%, respectively. This remote consanguinity value suggests that for any unrelated marriages in Lebanon, the mates could be related as third cousins or as second cousins once removed. Under the assumption that 25% of marriages occur between first cousins, the mean inbreeding value of 2.3% may explain the increased incidence of recessive disease in offspring. Our analysis reveals a common ancestral population in the four Lebanese communities we studied. © 2015 Macmillan Publishers Limited. All rights reserved. Source


Huang J.,Tongji University | Huang J.,Harvard University | Chen J.,Harvard University | Lathrop M.,Fondation Jean Dausset CEPH | Liang L.,Harvard University
Bioinformatics | Year: 2013

RNA sequencing data are becoming a major method of choice to study transcriptomes, including the mapping of gene expression quantitative trait loci (eQTLs). RNA sample contamination or swapping is a serious problem for downstream analysis and may result in false discovery and lose power to detect the true biological relationships. When genetic data are available, for example, in eQTL studies or samples have been previously genotyped or DNA sequenced, it is possible to combine genetic data and RNA-seq data to detect sample contamination and resolve sample swapping problems. In this article, we introduce a tool (IDCheck) that allows easy assessment of concordance between genotype (from SNP arrays or DNA sequencing) and gene expression (RNA-seq) samples. IDCheck compares the identity of RNA-seq reads and SNP genotypes using a likelihood-based method. Based on maximum likelihood estimates of relevant parameters, we can detect sample contamination and identify correct sample pairs when swapping occurs. Our tool provides an efficient and convenient way to evaluate and resolve these problems. © The Author 2013. Published by Oxford University Press. All rights reserved. Source


Gazal S.,French Institute of Health and Medical Research | Gazal S.,University Paris - Sud | Sahbatou M.,Fondation Jean Dausset CEPH | Babron M.-C.,French Institute of Health and Medical Research | And 5 more authors.
Bioinformatics | Year: 2014

Summary: FSuite is a user-friendly pipeline developed for exploiting inbreeding information derived from human genomic data. It can make use of single nucleotide polymorphism chip or exome data. Compared with other software, the advantage of FSuite is that it provides a complete suite of scripts to describe and use the inbreeding information. It includes a module to detect inbred individuals and estimate their inbreeding coefficient, a module to describe the proportion of different mating types in the population and the individual probability to be offspring of different mating types that can be useful for population genetic studies. It also allows the identification of shared regions of homozygosity between affected individuals (homozygosity mapping) that can be used to identify rare recessive mutations involved in monogenic or multifactorial diseases. © The Author 2014. Source

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