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Available from: Adam Kiezun, Jan 06, 2014
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    • "For complex diseases, WES can provide more evidence for causality compared to GWAS, assuming that the causal variants are exonic. This is because the latter uses linkage disequilibrium (LD) patterns between common markers [14] whereas WES directly associates the variant itself with the trait/disorder. Therefore using GWAS, especially in gene-dense regions, one cannot usually make conclusive judgements about which gene(s) is causal without further sequencing or functional analysis. "
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    ABSTRACT: Recent technological advances have created challenges for geneticists and a need to adapt to a wide range of new bioinformatics tools and an expanding wealth of publicly available data (e.g., mutation databases, and software). This wide range of methods and a diversity of file formats used in sequence analysis is a significant issue, with a considerable amount of time spent before anyone can even attempt to analyse the genetic basis of human disorders. Another point to consider that is although many possess " just enough " knowledge to analyse their data, they do not make full use of the tools and databases that are available and also do not fully understand how their data was created. The primary aim of this review is to document some of the key approaches and provide an analysis schema to make the analysis process more efficient and reliable in the context of discovering highly penetrant causal mutations/genes. This review will also compare the methods used to identify highly penetrant variants when data is obtained from consanguineous individuals as opposed to nonconsanguineous; and when Mendelian disorders are analysed as opposed to common-complex disorders.
    BioMed Research International 03/2015; DOI:10.1155/2015/923491 · 3.17 Impact Factor
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    • "Because the cost of whole-genome resequencing (WGS) is steadily decreasing, it should soon offer a comprehensive alternative to genotyping arrays with the theoretical advantage of allowing the detection of all individual polymorphisms and of making it easier to discover the causal variants underlying Mendelian or complex phenotypes or diseases (Kiezun et al. 2012; Faye et al. 2013). "
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    ABSTRACT: The number of polymorphisms identified with next-generation sequencing approaches depends directly on the sequencing depth and therefore on the experimental cost. Although higher levels of depth ensure more sensitive and more specific SNP calls, economic constraints limit the increase of depth for whole-genome resequencing (WGS). For this reason, capture resequencing is used for studies focusing on only some specific regions of the genome. However, several biases in capture resequencing are known to have a negative impact on the sensitivity of SNP detection. Within this framework, the aim of this study was to compare the accuracy of WGS and capture resequencing on SNP detection and genotype calling, which differ in terms of both sequencing depth and biases. Indeed, we have evaluated the SNP calling and genotyping accuracy in a WGS dataset (13X) and in a capture resequencing dataset (87X) performed on 11 individuals. The percentage of SNPs not identified due to a sevenfold sequencing depth decrease was estimated at 7.8% using a down-sampling procedure on the capture sequencing dataset. A comparison of the 87X capture sequencing dataset with the WGS dataset revealed that capture-related biases were leading with the loss of 5.2% of SNPs detected with WGS. Nevertheless, when considering the SNPs detected by both approaches, capture sequencing appears to achieve far better SNP genotyping, with about 4.4% of the WGS genotypes that can be considered as erroneous and even 10% focusing on heterozygous genotypes. In conclusion, WGS and capture deep sequencing can be considered equivalent strategies for SNP detection, as the rate of SNPs not identified because of a low sequencing depth in the former is quite similar to SNPs missed because of method biases of the latter. On the other hand, capture deep sequencing clearly appears more adapted for studies requiring great accuracy in genotyping.
    Animal Genetics 12/2014; 46(1). DOI:10.1111/age.12248 · 2.21 Impact Factor
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    • "Sequencing of the complete set of protein coding exons of an individual — whole exome sequencing (WES) — has enhanced the identification of genetic defect of rare diseases (Wan et al., 2012; Keller et al., 2013). These technologies can also be applied to decipher more common syndromes (Cirulli and Goldstein, 2010; Kiezun et al., 2012). Decision-making in oncology can now be based on the singular molecular signature of the tumor with implications in pathology and response to treatment or individual prognosis (Normanno et al., 2013). "
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