Copy number variation genotyping using family information

BACKGROUND: In recent years there has been a growing interest in the role of copy number variations (CNV) in genetic diseases. Though there has been rapid development of technologies and statistical methods devoted to detection in CNVs from array data, the inherent challenges in data quality associated with most hybridization techniques remains a challenging problem in CNV association studies. RESULTS: To help address these data quality issues in the context of family-based association studies, we introduce a statistical framework for the intensity-based array data that takes into account the family information for copy-number assignment. The method is an adaptation of traditional methods for modeling SNP genotype data that assume Gaussian mixture model, whereby CNV calling is performed for all family members simultaneously and leveraging within family-data to reduce CNV calls that are incompatible with Mendelian inheritance while still allowing de-novo CNVs. Applying this method to simulation studies and a genome-wide association study in asthma, we find that our approach significantly improves CNV calls accuracy, and reduces the Mendelian inconsistency rates and false positive genotype calls. The results were validated using qPCR experiments. CONCLUSIONS: In conclusion, we have demonstrated that the use of family information can improve the quality of CNV calling and hopefully give more powerful association test of CNVs

Copy number variation genotyping using family information

Abstract Background In recent years there has been a growing interest in the role of copy number variations (CNV) in genetic diseases. Though there has been rapid development of technologies and statistical methods devoted to detection in CNVs from array data, the inherent challenges in data quality associated with most hybridization techniques remains a challenging problem in CNV association studies. Results To help address these data quality issues in the context of family-based association studies, we introduce a statistical framework for the intensity-based array data that takes into account the family information for copy-number assignment. The method is an adaptation of traditional methods for modeling SNP genotype data that assume Gaussian mixture model, whereby CNV calling is performed for all family members simultaneously and leveraging within family-data to reduce CNV calls that are incompatible with Mendelian inheritance while still allowing de-novo CNVs. Applying this method to simulation studies and a genome-wide association study in asthma, we find that our approach significantly improves CNV calls accuracy, and reduces the Mendelian inconsistency rates and false positive genotype calls. The results were validated using qPCR experiments. Conclusions In conclusion, we have demonstrated that the use of family information can improve the quality of CNV calling and hopefully give more powerful association test of CNVs.http://deepblue.lib.umich.edu/bitstream/2027.42/112374/1/12859_2012_Article_5896.pd

Comparison of allelic imbalance in chromosomes 16 and 17 along with mutation in with -26 GA polymorphism background

<p><b>Copyright information:</b></p><p>Taken from "Implication of -26G>A 5' untranslated region polymorphism in susceptibility to sporadic breast cancer and its modulation by codon 72 Arg>Pro polymorphism"</p><p>http://breast-cancer-research.com/content/9/5/R71</p><p>Breast cancer research : BCR 2007;9(5):R71-R71.</p><p>Published online 18 Oct 2007</p><p>PMCID:PMC2242669.</p><p></p> values given are for overall distribution, G/G versus G/A, and A/A versus G/A

Effect of -26 G/A polymorphism on the 5' untranslated region secondary structure of RNA and stability analyzed by the RNAstructure program (version 4

<p><b>Copyright information:</b></p><p>Taken from "Implication of -26G>A 5' untranslated region polymorphism in susceptibility to sporadic breast cancer and its modulation by codon 72 Arg>Pro polymorphism"</p><p>http://breast-cancer-research.com/content/9/5/R71</p><p>Breast cancer research : BCR 2007;9(5):R71-R71.</p><p>Published online 18 Oct 2007</p><p>PMCID:PMC2242669.</p><p></p>3) and VRNAAFOLD (The European Molecular Biology Open Software Suite). The -26 position with G or A is indicated by arrows

Reporter gene assay with chimeric promoter and 5' untranslated region (UTR) with A or G at the -26 position (upper panel) and the effect of increasing the dose of adriamycin (0, 1, and 2

<p><b>Copyright information:</b></p><p>Taken from "Implication of -26G>A 5' untranslated region polymorphism in susceptibility to sporadic breast cancer and its modulation by codon 72 Arg>Pro polymorphism"</p><p>http://breast-cancer-research.com/content/9/5/R71</p><p>Breast cancer research : BCR 2007;9(5):R71-R71.</p><p>Published online 18 Oct 2007</p><p>PMCID:PMC2242669.</p><p></p>5 μM) (lower panel)