A. Janevski, V. Varadan, S. Kamalakaran, N. Banerjee, N. Dimitrova
{"title":"全基因组测序比较拷贝数变异","authors":"A. Janevski, V. Varadan, S. Kamalakaran, N. Banerjee, N. Dimitrova","doi":"10.1109/GENSiPS.2011.6169460","DOIUrl":null,"url":null,"abstract":"Whole genome sequencing enables a high resolution view of the human genome and enables unique insights into copy number variations on an unprecedented scale. Numerous tools and studies have already been introduced that provide confirmatory evidence and new genomic structure variation data in individuals as well as across populations. We utilize two such tools, CNV-seq and FREEC to compare their outputs when applied to five whole genome sequences representing four populations. We focus on the ability of these tools to detect segments from two sets of segments known to vary across populations, and discuss the direction and the challenges in developing tools that detect copy number variation in collections of human genomes.","PeriodicalId":181666,"journal":{"name":"2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Comparative copy number variation from whole genome sequencing\",\"authors\":\"A. Janevski, V. Varadan, S. Kamalakaran, N. Banerjee, N. Dimitrova\",\"doi\":\"10.1109/GENSiPS.2011.6169460\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Whole genome sequencing enables a high resolution view of the human genome and enables unique insights into copy number variations on an unprecedented scale. Numerous tools and studies have already been introduced that provide confirmatory evidence and new genomic structure variation data in individuals as well as across populations. We utilize two such tools, CNV-seq and FREEC to compare their outputs when applied to five whole genome sequences representing four populations. We focus on the ability of these tools to detect segments from two sets of segments known to vary across populations, and discuss the direction and the challenges in developing tools that detect copy number variation in collections of human genomes.\",\"PeriodicalId\":181666,\"journal\":{\"name\":\"2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GENSiPS.2011.6169460\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GENSiPS.2011.6169460","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparative copy number variation from whole genome sequencing
Whole genome sequencing enables a high resolution view of the human genome and enables unique insights into copy number variations on an unprecedented scale. Numerous tools and studies have already been introduced that provide confirmatory evidence and new genomic structure variation data in individuals as well as across populations. We utilize two such tools, CNV-seq and FREEC to compare their outputs when applied to five whole genome sequences representing four populations. We focus on the ability of these tools to detect segments from two sets of segments known to vary across populations, and discuss the direction and the challenges in developing tools that detect copy number variation in collections of human genomes.