• Genomics & Informatics
• /
• 제8권3호
• /
• pp.138-141
• /
• 2010

Together with single nucleotide polymorphism (SNP), copy number variations (CNV) are recognized to be the major component of human genetic diversity and used as a genetic marker in many disease association studies. Affymetrix Genome-wide SNP 5.0 is one of the commonly used SNP array platforms for SNP-GWAS as well as CNV analysis. However, there has been no report that validated the accuracy and reproducibility of CNVs identified by Affymetrix SNP array 5.0. In this study, we compared the characteristics of CNVs from the same set of genomic DNAs detected by three different array platforms; Affymetrix SNP array 5.0, Agilent 2X244K CNV array and NimbleGen 2.1M CNV array. In our analysis, Affymetrix SNP array 5.0 seems to detect CNVs in a reliable manner, which can be applied for association studies. However, for the purpose of defining CNVs in detail, Affymetrix Genome-wide SNP 5.0 might be relatively less ideal than NimbleGen 2.1M CNV array and Agilent 2X244K CNV array, which outperform Affymetrix array for defining the small-sized single copy variants. This result will help researchers to select a suitable array platform for CNV analysis.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2004년도 하계학술대회 논문집 Vol.5 No.2
• /
• pp.845-848
• /
• 2004

High throughput analysis using a DNA chip microarray is powerful tool in the post genome era. Less labor-intensive and lower cost-performance is required. Thus, this paper aims to develop the multi-channel type label-free DNA chip and detect SNP (Single nucleotide polymorphisms). At first, we fabricated a high integrated type DNA chip array by lithography technology. Various probe DNAs were immobilized on the microelectrode array. We succeeded to discriminate of DNA hybridization between target DNA and mismatched DNA on microarray after immobilization of a various probe DNA and hybridization of label-free target DNA on the electrodes simultaneously. This method is based on redox of an electrochemical ligand.

• Genomics & Informatics
• /
• 제10권3호
• /
• pp.194-199
• /
• 2012

In addition to single-nucleotide polymorphisms (SNP), copy number variation (CNV) is a major component of human genetic diversity. Among many whole-genome analysis platforms, SNP arrays have been commonly used for genomewide CNV discovery. Recently, a number of CNV defining algorithms from SNP genotyping data have been developed; however, due to the fundamental limitation of SNP genotyping data for the measurement of signal intensity, there are still concerns regarding the possibility of false discovery or low sensitivity for detecting CNVs. In this study, we aimed to verify the effect of combining multiple CNV calling algorithms and set up the most reliable pipeline for CNV calling with Affymetrix Genomewide SNP 5.0 data. For this purpose, we selected the 3 most commonly used algorithms for CNV segmentation from SNP genotyping data, PennCNV, QuantiSNP; and BirdSuite. After defining the CNV loci using the 3 different algorithms, we assessed how many of them overlapped with each other, and we also validated the CNVs by genomic quantitative PCR. Through this analysis, we proposed that for reliable CNV-based genomewide association study using SNP array data, CNV calls must be performed with at least 3 different algorithms and that the CNVs consistently called from more than 2 algorithms must be used for association analysis, because they are more reliable than the CNVs called from a single algorithm. Our result will be helpful to set up the CNV analysis protocols for Affymetrix Genomewide SNP 5.0 genotyping data.

• 한국전기전자재료학회논문지
• /
• 제17권4호
• /
• pp.410-414
• /
• 2004

High throughput analysis using a DNA chip microarray is powerful tool in the post genome era. Less labor-intensive and lower cost-performance is required. Thus, this paper aims to develop the multi-channel type label-free DNA chip and detect SNP (Single nucleotide polymorphisms). At first, we fabricated a high integrated type DNA chip array by lithography technology. Various probe DNAs were immobilized on the microelectrode array. We succeeded to discriminate of DNA hybridization between target DNA and mismatched DNA on microarray after immobilization of a various probe DNA and hybridization of label-free target DNA on the electrodes simultaneously. This method is based on redox of an electrochemical ligand.

• Asian-Australasian Journal of Animal Sciences
• /
• 제23권7호
• /
• pp.833-847
• /
• 2010

In the past decade, there have been many advances in whole-genome sequencing in domestic animals, as well as the development of "next-generation" sequencing technologies and high-throughput genotyping platforms. Consequently, these advances have led to the creation of the high-density SNP array as a state-of-the-art tool for genetics and genomics analyses of domestic animals. The emergence and utilization of SNP arrays will have significant impacts not only on the scale, speed, and expense of SNP genotyping, but also on theoretical and applied studies of quantitative genetics, population genetics and molecular evolution. The most promising applications in agriculture could be genome-wide association studies (GWAS) and genomic selection for the improvement of economically important traits. However, some challenges still face these applications, such as incorporating linkage disequilibrium (LD) information from HapMap projects, data storage, and especially appropriate statistical analyses on the high-dimensional, structured genomics data. More efforts are still needed to make better use of the high-density SNP arrays in both academic studies and industrial applications.

• Genomics & Informatics
• /
• 제6권4호
• /
• pp.231-234
• /
• 2008

Precise and reliable identification of CNV is still important to fully understand the effect of CNV on genetic diversity and background of complex diseases. SNP marker has been used frequently to detect CNVs, but the analysis of SNP chip data for identifying CNV has not been well established. We compared various normalization methods for CNV analysis and suggest optimal normalization procedure for reliable CNV call. Four normal Koreans and NA10851 HapMap male samples were genotyped using Affymetrix Genome-Wide Human SNP array 5.0. We evaluated the effect of median and quantile normalization to find the optimal normalization for CNV detection based on SNP array data. We also explored the effect of Robust Multichip Average (RMA) background correction for each normalization process. In total, the following 4 combinations of normalization were tried: 1) Median normalization without RMA background correction, 2) Quantile normalization without RMA background correction, 3) Median normalization with RMA background correction, and 4) Quantile normalization with RMA background correction. CNV was called using SW-ARRAY algorithm. We applied 4 different combinations of normalization and compared the effect using intensity ratio profile, box plot, and MA plot. When we applied median and quantile normalizations without RMA background correction, both methods showed similar normalization effect and the final CNV calls were also similar in terms of number and size. In both median and quantile normalizations, RMA backgroundcorrection resulted in widening the range of intensity ratio distribution, which may suggest that RMA background correction may help to detect more CNVs compared to no correction.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2004년도 하계학술대회 논문집 C
• /
• pp.2128-2130
• /
• 2004

High throughput analysis using a DNA chip microarray is powerful tool in the post genome era. Less labor-intensive and lower cost-performance is required. Thus, this paper aims to develop the multi-channel type label-free DNA chip and detect SNP (Single nucleotide polymorphisms). At first, we fabricated a high integrated type DNA chip array by lithography technology. Various probe DNAs were immobilized on the microelectrode array. We succeeded to discriminate of DNA hybridization between target DNA and mismatched DNA on microarray after immobilization of a various probe DNA and hybridization of label-free target DNA on the electrodes simultaneously. This method is based on redox of an electrochemical ligand.

• 한국전기전자재료학회:학술대회논문집
• /
• 한국전기전자재료학회 2006년도 하계학술대회 논문집 Vol.7
• /
• pp.410-411
• /
• 2006

High throughput analysis using a DNA chip microarray is powerful tool in the post genome era. Less labor-intensive and lower cost-performance is required. Thus, this paper aims to develop the multi-channel type label-free DNA chip and detect SNP (Single nucleotide polymorphisms). At first, we fabricated a high integrated type DNA chip array by lithography technology. Various probe DNAs were immobilized on the microelectrode array. We succeeded to discriminate of DNA hybridization between target DNA and mismatched DNA on microarray after immobilization of a various probe DNA and hybridization of label-free target DNA on. the electrodes simultaneously. This method is based on redox of an electrochemical ligand.

• BMB Reports
• /
• 제46권6호
• /
• pp.305-309
• /
• 2013

The determination of relatedness between individuals in a family is crucial in analysis of common complex diseases. We present a method to infer close inter-familial relationships based on SNP genotyping data and provide the relationship coefficient of kinship in Korean families. We obtained blood samples from 43 Korean individuals in two families. SNP data was obtained using the Affymetrix Genome-wide Human SNP array 6.0 and the Illumina Human 1M-Duo chip. To measure the kinship coefficient with the SNP genotyping data, we considered all possible pairs of individuals in each family. The genetic distance between two individuals in a pair was determined using the allele sharing distance method. The results show that genetic distance is proportional to the kinship coefficient and that a close degree of kinship can be confirmed with SNP genotyping data. This study represents the first attempt to identify the genetic distance between very closely related individuals.

• Journal of Animal Science and Technology
• /
• 제64권5호
• /
• pp.830-841
• /
• 2022

Genetic analysis has great potential as a tool to differentiate between different species and breeds of livestock. In this study, the optimal combinations of single nucleotide polymorphism (SNP) markers for discriminating the Yeonsan Ogye chicken (Gallus gallus domesticus) breed were identified using high-density 600K SNP array data. In 3,904 individuals from 198 chicken breeds, SNP markers specific to the target population were discovered through a case-control genome-wide association study (GWAS) and filtered out based on the linkage disequilibrium blocks. Significant SNP markers were selected by feature selection applying two machine learning algorithms: Random Forest (RF) and AdaBoost (AB). Using a machine learning approach, the 38 (RF) and 43 (AB) optimal SNP marker combinations for the Yeonsan Ogye chicken population demonstrated 100% accuracy. Hence, the GWAS and machine learning models used in this study can be efficiently utilized to identify the optimal combination of markers for discriminating target populations using multiple SNP markers.