Simultaneous Discovery and Testing of Deletions for Disease Association in SNP Genotyping Studies

Kohler, Jared; Cutler, David J.

doi:10.1086/520823

Cited by 17 publications

(18 citation statements)

References 67 publications

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“…These concurrent studies showed that non-diseased individuals carry many various-sized genomic deletions with high population frequencies. Recently, Amos et al (2003) and Kohler and Cutler (2007) proposed likelihood-based statistical methods for detecting disease associated deletions from familial SNP genotype data. Their methods harnessed the information on SNP transmission patterns between true genotypes and observed (miscalled) genotypes within parent-offspring trios to detect deletions.…”

Section: Introductionmentioning

confidence: 99%

Detection of disease-associated deletions in case–control studies using SNP genotypes with application to rheumatoid arthritis

Shete

Chen

et al. 2009

Hum Genet

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Genomic deletions have long been known to play a causative role in microdeletion syndromes. Recent whole-genome genetic studies have shown that deletions can increase the risk for several psychiatric disorders, suggesting that genomic deletions play an important role in the genetic basis of complex traits. However, the association between genomic deletions and common, complex diseases has not yet been systematically investigated in gene mapping studies. Likelihood-based statistical methods for identifying disease-associated deletions have recently been developed for familial studies of parent-offspring trios. The purpose of this study is to develop statistical approaches for detecting genomic deletions associated with complex disease in case-control studies. Our methods are designed to be used with dense single nucleotide polymorphism (SNP)

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Section: Introductionmentioning

confidence: 99%

Detection of disease-associated deletions in case–control studies using SNP genotypes with application to rheumatoid arthritis

Shete

Chen

et al. 2009

Hum Genet

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“…In particular, null alleles are an indication of a possible deletion. In humans, incompatibilities and missing values in genotype data from high-density SNP arrays (~1 million SNPs) have been used to map hundreds of deletions in the range of 1−1000 kb (Conrad et al 2006; McCarroll et al 2006; Kohler and Cutler 2007). …”

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confidence: 99%

Identification of Null Alleles and Deletions from SNP Genotypes for an Intercross Between Domestic and Wild Chickens

Crooks

Carlborg

Marklund

et al. 2013

G3 Genes|Genomes|Genetics

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We analyzed genotypes from ~10K single-nucleotide polymorphisms (SNPs) in two families of an F2 intercross between Red Junglefowl and White Leghorn chickens. Possible null alleles were found by patterns of incompatible and missing genotypes. We estimated that 2.6% of SNPs had null alleles compared with 2.3% with genotyping errors and that 40% of SNPs in which a parent and offspring were genotyped as different homozygotes had null alleles. Putative deletions were identified by null alleles at adjacent markers. We found two candidate deletions that were supported by fluorescence intensity data from a 60K SNP chip. One of the candidate deletions was from the Red Junglefowl, and one was present in both the Red Junglefowl and White Leghorn. Both candidate deletions spanned protein-coding regions and were close to a previously detected quantitative trait locus affecting body weight in this population. This study demonstrates that the ~50K SNP genotyping arrays now available for several agricultural species can be used to identify null alleles and deletions in data from large families. We suggest that our approach could be a useful complement to linkage analysis in experimental crosses.

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“…Modeling the transmission can thus combine the signal across individuals and increase the resolution of our method. Furthermore, in such a model we can include NMIs and departure from HWE to directly call carriers [Kohler and Cutler, 2007].…”

Section: Discussionmentioning

confidence: 99%

“…Thus, many carriers in the parental generation will not be identified, making it challenging to apply methods commonly used for family data to test for association between a phenotype and a deletion inferred from NMIs, as such tests rely on transmission distortion [Spielman and Ewens, 1996;Horvath et al, 2001]. Kohler and Cutler [2007] have recently developed a method to overcome this limitation, combining NMIs, deviations from Hardy-Weinberg Equilibrium (HWE), and frequency of missing data. However it is not clear how robust this method is to population genetic effects affecting HWE such as inbreeding and population substructure.…”

Section: Introductionmentioning

confidence: 99%

Bayesian EM algorithm for scoring polymorphic deletions from SNP data and application to a common CNV on 8q24

Zöllner

Stewart

et al. 2008

Genetic Epidemiology

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Copy number variations (CNVs) in the human genome provide exciting candidates for functional polymorphisms. Hence, we now assess association between CNV carrier status and diseases status by evaluating the signal intensity of SNP genotyping assays. Here, we present a novel statistical method designed to perform such inference and apply this method to a known CNV in a bipolar disorder linkage region. Using Bayesian computations we calculate the posterior probability for carrier status of a CNV in each individual of a sample by jointly analyzing genotype information and hybridization intensity. We model the signal intensity as a mixture of normal distributions, allowing for locus-specific and allele-specific distributions. Using an expectation maximization algorithm we estimate the parameters of these distributions and use these estimates for inferring carrier status of each individual and for the boundaries of the CNV. We applied the method to a sample of 3,512 individuals to a previously described common deletion on 8q24, a region consistently showing linkage to bipolar disorder, and unambiguously inferred 172 heterozygous and 1 homozygous deletion carrier. We observed no significant association between bipolar disorder and carrier status. We carefully assessed the validity of the inferred carrier status and observed no indication of errors. Furthermore, the algorithm precisely identifies the boundaries of the CNV. Finally, we assessed the power of this algorithm to detect shorter CNVs by sub-sampling from the SNPs covered by this deletion, demonstrating that our EM algorithm produces precise estimates of carrier status.

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Simultaneous Discovery and Testing of Deletions for Disease Association in SNP Genotyping Studies

Cited by 17 publications

References 67 publications

Detection of disease-associated deletions in case–control studies using SNP genotypes with application to rheumatoid arthritis

Detection of disease-associated deletions in case–control studies using SNP genotypes with application to rheumatoid arthritis

Identification of Null Alleles and Deletions from SNP Genotypes for an Intercross Between Domestic and Wild Chickens

Bayesian EM algorithm for scoring polymorphic deletions from SNP data and application to a common CNV on 8q24

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