Project description:Custom Affymetrix SNP used to assay 24 mothers for desired variants. Data processed using the Affymetrix SNP Genotyping Console (Version 4.2, Affymetrix Inc., Santa Clara, CA, USA).
Project description:Genome-wide SNP genotyping array can genotyped SNP highthroughly. It can be used in many aspects, such as phylogeny relationships, genome-wide association studies, copy number identification.
Project description:Estimating the relationships between individuals is one of the fundamental challenges in many fields. In particular, relationship estimation could provide valuable information for missing persons cases. The recently developed investigative genetic genealogy approach uses high-density single nucleotide polymorphisms (SNPs) to determine close and more distant relationships, in which hundreds of thousands to tens of millions of SNPs are generated either by microarray genotyping or whole-genome sequencing. The current studies usually assume the SNP profiles were generated with minimum errors. However, in the missing person cases, the DNA samples can be highly degraded, and the SNP profiles generated from these samples usually contain lots of errors. In this study, a robust machine learning approach was developed for estimating the relationships with high error SNP profiles. In this approach, a hierarchical classification strategy was employed first to classify the relationships by degree and then the relationship types within each degree separately. As for each classification, feature selection was implemented to gain better performance. Both simulated and real data sets with various genotyping error rates were utilized in evaluating this approach, and the accuracies of this approach were higher than individual measures; namely, this approach was more accurate and robust than the individual measures for SNP profiles with genotyping errors. In addition, the highest accuracy could be obtained by providing the same genotyping error rates in train and test sets, and thus estimating genotyping errors of the SNP profiles is critical to obtaining high accuracy of relationship estimation.
Project description:High density genotyping of 7 affected and 3 unaffected family members was performed using the Illumina Omni2.5-8 v1.3 BeadChip SNP.
Project description:Optimize SNP genotyping probes and demonstrate a new P. falciparum microarray platform that includes CGH and resequencing probes on the same chip
Project description:A consanguineous family segregating anhidrosis (recessive, familial) Shared homozygous regions were identified by comparing SNP genotyping results from four affected family members
Project description:Comparison of Genotyping using pooled DNA samples (Allelotyping) and Individual Genotyping using the Affymetrix Genome-Wide Human SNP Array 6.0 In this study, data from 100 DNA samples individually genotyped with the Affymetrix Genome-Wide Human SNP Array 6.0 were used to estimate the error of the pooling approach by comparing the results with those obtained using the same array type but DNA pools each composed of 50 of the same samples. Newly developed and established methods for signal intensity correction were applied. Furthermore, the relative allele intensity signals (RAS) obtained by allelotyping were compared to the corresponding values derived from individual genotyping. Similarly, differences in RAS values between pools were determined and compared.
Project description:SNP genotyping was used to determine if the free living Highland Wild dogs of Papua, Indonesia are the ansestors of captive New Guinea Singing Dogs.
Project description:Renal tumors with complex morphology require extensive workup for accurate classification. Chromosomal aberrations that define subtypes of renal epithelial neoplasms have been reported. We explored if whole-genome chromosome copy number and loss-of-heterozygosity analysis with single nucleotide polymorphism (SNP) arrays can be used to identify these aberrations. Keywords: Chromosome copy number and LOH analysis with SNP Genotyping Arrays