Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Keywords: Germany ; DISEASE ; POPULATION ; GENE ; COMPLEX ; COMPLEXES ; MARKER ; ASSOCIATION ; LINKAGE ; statistics ; LENGTH ; PHENOTYPE ; case-control studies ; RECONSTRUCTION ; case-control study ; RE ; interaction ; case control studies ; HAPLOTYPE ; complex disease ; haplotype sharing ; mantel statistics ; TESTS ; haplotype-sharing ; SHARING ANALYSIS ; POWER ; SIZE
    Abstract: We applied a new approach based on Mantel statistics to analyze the Genetic Analysis Workshop 14 simulated data with prior knowledge of the answers. The method was developed in order to improve the power of a haplotype sharing analysis for gene mapping in complex disease. The new statistic correlates genetic similarity and phenotypic similarity across pairs of haplotypes from case-control studies. The genetic similarity is measured as the shared length between haplotype pairs around a genetic marker. The phenotypic similarity is measured as the mean corrected cross-product based on the respective phenotypes. Cases with phenotype P1 and unrelated controls were drawn from the population of Danacaa. Power to detect main effects was compared to the X-2-test for association based on 3-marker haplotypes and a global permutation test for haplotype association to test for main effects. Power to detect gene x gene interaction was compared to unconditional logistic regression. The results suggest that the Mantel statistics might be more powerful than alternative tests
    Type of Publication: Journal article published
    PubMed ID: 16451684
    Signatur Availability
    BibTip Others were also interested in ...
  • 2
  • 3
    Keywords: human ; DISEASE ; GENE ; GENES ; GENOME ; TISSUE ; HEART ; TIME ; MESSENGER-RNA ; ELEMENT ; ISOFORM ; MOUSE ; ELEMENTS ; genetics ; statistics ; DATABASE ; MUSCLE ; heredity ; MOLECULAR-CLONING ; analysis ; E ; ENGLAND ; transcriptome ; NOV ; GENOMES ; EXONS ; ALU SEQUENCE ; HUMAN TRANSCRIPTOME ; REPBASE UPDATE ; REPETITIVE ELEMENTS ; SPLICE-MEDIATED INSERTION
    Abstract: Background: Transposed elements (TEs) are known to affect transcriptomes, because either new exons are generated from intronic transposed elements (this is called exonization), or the element inserts into the exon, leading to a new transcript. Several examples in the literature show that isoforms generated by an exonization are specific to a certain tissue (for example the heart muscle) or inflict a disease. Thus, exonizations can have negative effects for the transcriptome of an organism. Results: As we aimed at detecting other tissue-or tumor-specific isoforms in human and mouse genomes which were generated through exonization of a transposed element, we designed the automated analysis pipeline SERpredict (SER = (S) under bar pecific (E) under bar xonized (R) under bar etroelement) making use of Bayesian Statistics. With this pipeline, we found several genes in which a transposed element formed a tissue-or tumor-specific isoform. Conclusion: Our results show that SERpredict produces relevant results, demonstrating the importance of transposed elements in shaping both the human and the mouse transcriptomes. The effect of transposed elements on the human transcriptome is several times higher than the effect on the mouse transcriptome, due to the contribution of the primate-specific Alu elements
    Type of Publication: Journal article published
    PubMed ID: 17986331
    Signatur Availability
    BibTip Others were also interested in ...
  • 4
    Keywords: RECEPTOR ; CANCER ; Germany ; COMMON ; DISEASE ; RISK ; GENE ; ASSOCIATION ; LINKAGE ; polymorphism ; POLYMORPHISMS ; single nucleotide polymorphism ; SUSCEPTIBILITY ; VARIANTS ; BREAST ; breast cancer ; BREAST-CANCER ; DELETION ; IDENTIFICATION ; COPY NUMBER ; DESIGN ; DIFFERENCE ; NUMBER ; genetics ; DELETIONS ; cancer risk ; HUMAN GENOME ; LINKAGE DISEQUILIBRIUM ; Jun ; case-control studies ; INDIVIDUALS ; heredity ; SINGLE ; case control study ; case-control study ; ASSOCIATIONS ; RE ; VARIANT ; REARRANGEMENT ; case control studies ; analysis ; single-nucleotide ; SEGMENTAL DUPLICATIONS ; CANCER-RISK ; genomic ; FRAGMENT ; COPY-NUMBER VARIATION ; - ; STRUCTURAL VARIATION
    Abstract: Background: Copy number polymorphisms caused by genomic rearrangements like deletions, make a significant contribution to the genomic differences between two individuals and may add to disease predisposition. Therefore, genotyping of such deletion polymorphisms in case-control studies could give important insights into risk associations. Results: We mapped the breakpoints and developed a fluorescent fragment analysis for a deletion disrupting the TRY6 gene to exemplify a quick and cheap genotyping approach for such structural variants. We showed that the deletion is larger than predicted and encompasses also the pseudogene TRY5. We performed a case-control study to test an association of the TRY6 deletion polymorphism with breast cancer using a single nucleotide polymorphism which is in 100% linkage disequilibrium with the deletion. We did not observe an effect of the deletion on breast cancer risk (OR 1.05, 95% CI 0.71 - 1.56). Conclusion: Although we did not observe an association between the TRY6 deletion polymorphism and breast cancer risk, the identification and investigation of further deletions using the present approach may help to elucidate their effect on disease susceptibility
    Type of Publication: Journal article published
    PubMed ID: 17598925
    Signatur Availability
    BibTip Others were also interested in ...
  • 5
    Keywords: Germany ; MODEL ; DISEASE ; GENE ; SAMPLE ; IMPACT ; ASSOCIATION ; FREQUENCIES ; PERFORMANCE ; genetics ; RATES ; REPLICATION ; UNCERTAINTY ; transmission/disequilibrium test ; TESTS ; ERROR ; HARDY-WEINBERG EQUILIBRIUM ; ROBUST ; CONTROL GENETIC ASSOCIATION ; MISCLASSIFICATION ; TAGGING SNP SELECTION
    Abstract: Background: We investigated the influence of genotyping errors on the type I error rate and empirical power of two haplotype based association methods applied to candidate regions. We compared the performance of the Mantel Statistic Using Haplotype Sharing and the haplotype frequency based score test with that of the Armitage trend test. Our study is based on 1000 replication of simulated case-control data settings with 500 cases and 500 controls, respectively. One of the examined markers was set to be the disease locus with a simulated odds ratio of 3. Differential and non-differential genotyping errors were introduced following a misclassification model with varying mean error rates per locus in the range of 0.2% to 15.6%. Results: We found that the type I error rate of all three test statistics hold the nominal significance level in the presence of nondifferential genotyping errors and low error rates. For high and differential error rates, the type I error rate of all three test statistics was inflated, even when genetic markers not in Hardy-Weinberg Equilibrium were removed. The empirical power of all three association test statistics remained high at around 89% to 94% when genotyping error rates were low, but decreased to 48% to 80% for high and nondifferential genotyping error rates. Conclusion: Currently realistic genotyping error rates for candidate gene analysis (mean error rate per locus of 0.2%) pose no significant problem for the type I error rate as well as the power of all three investigated test statistics
    Type of Publication: Journal article published
    PubMed ID: 19178712
    Signatur Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...