• Proceedings of the Korea Information Processing Society Conference
• /
• 2008.11a
• /
• pp.356-359
• /
• 2008

최근 생물정보학 분야에서 인간 유전체에 존재하는 CNV(copy number variation)에 관한 연구가 주목 받고 있다. CNV 영역은 1kbp-3Mbp 사리의 서열이 반복되거나 결실되는 변이 영역으로 정의된다. 우리는 선행연구에서 기가 시퀀싱(giga sequencing)의 결과 산출되는 DNA 서열조각인 리드(read)를 레퍼런스 시퀀스에 서열 정렬하여 CNV 영역을 찾아내는 새로운 CNV 검색 방식을 제안하였다. 후속 연구로서 본 논문에서는 DNA 서열에 존재하는 repeat 영역 문제를 해결하기 위한 새로운 방안을 제안하고, 리드의 출현 빈도 정보를 분석하여 CNV 영역을 찾아내는 CNV 영역 검색 알고리즘을 보인다. 제안된 알고리즘 Gaussian 분포를 갖는 출현 빈도 정보로부터 통계적 유의성을 갖는 영역을 추출하여 CNV 영역후보로 하고, 다음 경제 과정을 거쳐 최종의 CNV 영역을 추출한다. 성능 평가를 위하여 프로토타임 시스템을 개발하였으며, 시뮬레이션 실험을 수행하였다. 실험 결과에 의하여 제안된 방식은 반복되거나 결실되는 형태의 CNV 영역을 효율적으로 검출하며, 또한 다양한 크기의 CNV 영역을 효율적으로 검출할 수 있음을 입증한다.

• Genomics & Informatics
• /
• v.10 no.3
• /
• 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.

• Journal of KIISE:Databases
• /
• v.41 no.4
• /
• pp.249-255
• /
• 2014

Copy number variations(CNVs) are a recently recognized class of human structural variations and are associated with a variety of human diseases, including cancer. To find important cancer genes, researchers identify novel CNVs in patients with a particular cancer and analyze large amounts of genomic and clinical data. We present a tool called CNVDAT which is able to detect CNVs from NGS data and systematically analyze the genomic and clinical data associated with variations. CNVDAT consists of two modules, CNV Detection Engine and Sequence Analyser. CNV Detection Engine extracts CNVs by using the multi-resolution system of scale-space filtering, enabling the detection of the types and the exact locations of CNVs of all sizes even when the coverage level of read data is low. Sequence Analyser is a user-friendly program to view and compare variation regions between tumor and matched normal samples. It also provides a complete analysis function of refGene and OMIM data and makes it possible to discover CNV-gene-phenotype relationships. CNVDAT source code is freely available from http://dblab.hallym.ac.kr/CNVDAT/.

• The KIPS Transactions:PartD
• /
• v.18D no.2
• /
• pp.89-100
• /
• 2011

The CNV (Copy Number Variation) which is one of the genetic structural variations in human genome is closely related with the function of gene. In particular, the genome-wide association studies for genetic diseased persons have been researched. However, there have been few studies which infer the genetic function of CNV with normal human. In this paper, we propose the analysis method to reveal the functional relationship between common CNV and genes without considering their genomic loci. To achieve that, we propose the data integration method for heterogeneity biological data and novel measurement which can calculate the correlation between common CNV and genes. To verify the significance of proposed method, we has experimented several verification tests with GO database. The result showed that the novel measurement had enough significance compared with random test and the proposed method could systematically produce the candidates of genetic function which have strong correlation with common CNV.

• The KIPS Transactions:PartD
• /
• v.16D no.5
• /
• pp.661-672
• /
• 2009

Recently it was found that various genetic structural variations such as CNV(copy number variation) exist in the human genome, and these variations are closely related with disease susceptibility, reaction to treatment, and genetic characteristics. In this paper we propose a new CNV detection algorithm using millions of short DNA sequences generated by giga-sequencing technology. Our method maps the DNA sequences onto the reference sequence, and obtains the occurrence frequency of each read in the reference sequence. And then it detects the statistically significant regions which are longer than 1Kbp as the candidate CNV regions by analyzing the distribution of the occurrence frequency. To select a proper read alignment method, several methods are employed in our algorithm, and the performances are compared. To verify the superiority of our approach, we performed extensive experiments. The result of simulation experiments (using a reference sequence, build 35 of NCBI) revealed that our approach successfully finds all the CNV regions that have various shapes and arbitrary length (small, intermediate, or large size).

• Asian-Australasian Journal of Animal Sciences
• /
• v.27 no.12
• /
• pp.1691-1694
• /
• 2014

Copy number variation (CNV) or single nucleotide phlyorphism (SNP) is useful genetic resource to aid in understanding complex phenotypes or deseases susceptibility. Although thousands of CNVs and SNPs are currently avaliable in the public databases, they are somewhat difficult to use for analyses without visualization tools. We developed a web-based tool called the VCS (visualization of CNV or SNP) to visualize the CNV or SNP detected. The VCS tool can assist to easily interpret a biological meaning from the numerical value of CNV and SNP. The VCS provides six visualization tools: i) the enrichment of genome contents in CNV; ii) the physical distribution of CNV or SNP on chromosomes; iii) the distribution of log2 ratio of CNVs with criteria of interested; iv) the number of CNV or SNP per binning unit; v) the distribution of homozygosity of SNP genotype; and vi) cytomap of genes within CNV or SNP region.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2001.05a
• /
• pp.308-312
• /
• 2001

본 연구에서는 사상관련전위인 수반음성변동(CNV)을 이용하여 쾌/불쾌 향의 영향을 평가하고자 하였다. 즉, 건강한 20대 성인을 대상으로 쾌한 향(레몬)과 불쾌한 향(E3) 자극에 따른 CNV의 전기성분 및 후기성분의 변화를 대뇌부위별, 가산횟수별로 비교 분석하였고, 쾌/불쾌 향의 자극 반복에 따른 주관적 평가도 부가하여 검토하였다. 그 결과, 쾌/불쾌 향은 CNV 후기성분의 중심엽 부위에서 10∼15회 가산평균의 경우 정량적으로 구별될 수 있는 가능성을 보였고, 주관적인 평가에서는 반복 자극횟수가 증가함에 따라 쾌/불쾌감이 저하하는 것을 알 수 있었다.

• Genomics & Informatics
• /
• v.12 no.4
• /
• pp.136-144
• /
• 2014

Besides single-nucleotide variants in the human genome, large-scale genomic variants, such as copy number variations (CNVs), are being increasingly discovered as a genetic source of human diversity and the pathogenic factors of diseases. Recent experimental findings have shed light on the links between different genome architectures and CNV mutagenesis. In this review, we summarize various genomic features and discuss their contributions to CNV formation. Genomic repeats, including both low-copy and high-copy repeats, play important roles in CNV instability, which was initially known as DNA recombination events. Furthermore, it has been found that human genomic repeats can also induce DNA replication errors and consequently result in CNV mutations. Some recent studies showed that DNA replication timing, which reflects the high-order information of genomic organization, is involved in human CNV mutations. Our review highlights that genome architecture, from DNA sequence to high-order genomic organization, is an important molecular factor in CNV mutagenesis and human genomic instability.

• Korean Journal of Veterinary Research
• /
• v.39 no.2
• /
• pp.294-300
• /
• 1999

In this study PRRSV was isolated from serum of an infected pig and designated as CNV-1, ORF4 gene was sequenced, and the nucleotide sequence, deduced amino acid sequence and the amino acid sequence of the neutralizing domain was compared with other PRRSV Strains. ORF4 gene of the Korean isolate PRRSV CNV-1 was shown to be 537bp in length, which is the same as US strain ISU55 but 21bp longer than another US strain MN1b, and 15bp shorter than European strain LV. The homologies of the nucleotide sequences between the Korean isolate CNV-1 and the US strains ISU55, MN1b and European strain LV were 91.8%, 88.1%, 67.6%, respectively, and the homologies of the deduced amino acid sequences were 94.4%, 84.4%, 68.5%, respectively. The neutralizing domain of the CNV-1 was shown to be 36 amino acids in length which is the same as ISU55, MN1b, but 4 amino acids shorter than that of the neutralizing domain reported in LV. The homologies of the amino acid sequences of the neutralizing domain between the Korean isolate CNV-1 and the US strains ISU55, MN1b and European strain LV were 92.5%, 85%, 57.5%, respectively. The molecular characteristics of ORF4 gene of the Korean isolate PRRSV CNV-1 shown in this study suggests that the CNV-1 is genetically closer to the US strains. Also the wide variation of the neutralizing domain between the CNV-1 and LV suggests that there is substantial immunogenic variation between the two strains.

• Genomics & Informatics
• /
• v.8 no.3
• /
• 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.