{"title":"来自多个单细胞的细菌基因组的从头共组装","authors":"Narjes S. Movahedi, Elmira Forouzmand, H. Chitsaz","doi":"10.1109/BIBM.2012.6392618","DOIUrl":null,"url":null,"abstract":"Recent progress in DNA amplification techniques, particularly multiple displacement amplification (MDA), has made it possible to sequence and assemble bacterial genomes from a single cell. However, the quality of single cell genome assembly has not yet reached the quality of normal multiceli genome assembly due to the coverage bias and errors caused by MDA. Using a template of more than one cell for MDA or combining separate MDA products has been shown to improve the result of genome assembly from few single cells, but providing identical single cells, as a necessary step for these approaches, is a challenge. As a solution to this problem, we give an algorithm for de novo co-assembly of bacterial genomes from multiple single cells. Our novel method not only detects the outlier cells in a pool, it also identifies and eliminates their genomic sequences from the final assembly. Our proposed co-assembly algorithm is based on colored de Bruijn graph which has been recently proposed for de novo structural variation detection. Our results show that de novo co-assembly of bacterial genomes from multiple single cells outperforms single cell assembly of each individual one in all standard metrics. Moreover, co-assembly outperforms mixed assembly in which the input datasets are simply concatenated. We implemented our algorithm in a software tool called HyDA which is available from http://compbio.cs.wayne.edu/software/hyda.","PeriodicalId":6392,"journal":{"name":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"De novo co-assembly of bacterial genomes from multiple single cells\",\"authors\":\"Narjes S. Movahedi, Elmira Forouzmand, H. Chitsaz\",\"doi\":\"10.1109/BIBM.2012.6392618\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recent progress in DNA amplification techniques, particularly multiple displacement amplification (MDA), has made it possible to sequence and assemble bacterial genomes from a single cell. However, the quality of single cell genome assembly has not yet reached the quality of normal multiceli genome assembly due to the coverage bias and errors caused by MDA. Using a template of more than one cell for MDA or combining separate MDA products has been shown to improve the result of genome assembly from few single cells, but providing identical single cells, as a necessary step for these approaches, is a challenge. As a solution to this problem, we give an algorithm for de novo co-assembly of bacterial genomes from multiple single cells. Our novel method not only detects the outlier cells in a pool, it also identifies and eliminates their genomic sequences from the final assembly. Our proposed co-assembly algorithm is based on colored de Bruijn graph which has been recently proposed for de novo structural variation detection. Our results show that de novo co-assembly of bacterial genomes from multiple single cells outperforms single cell assembly of each individual one in all standard metrics. Moreover, co-assembly outperforms mixed assembly in which the input datasets are simply concatenated. We implemented our algorithm in a software tool called HyDA which is available from http://compbio.cs.wayne.edu/software/hyda.\",\"PeriodicalId\":6392,\"journal\":{\"name\":\"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2012.6392618\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Bioinformatics and Biomedicine Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2012.6392618","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
De novo co-assembly of bacterial genomes from multiple single cells
Recent progress in DNA amplification techniques, particularly multiple displacement amplification (MDA), has made it possible to sequence and assemble bacterial genomes from a single cell. However, the quality of single cell genome assembly has not yet reached the quality of normal multiceli genome assembly due to the coverage bias and errors caused by MDA. Using a template of more than one cell for MDA or combining separate MDA products has been shown to improve the result of genome assembly from few single cells, but providing identical single cells, as a necessary step for these approaches, is a challenge. As a solution to this problem, we give an algorithm for de novo co-assembly of bacterial genomes from multiple single cells. Our novel method not only detects the outlier cells in a pool, it also identifies and eliminates their genomic sequences from the final assembly. Our proposed co-assembly algorithm is based on colored de Bruijn graph which has been recently proposed for de novo structural variation detection. Our results show that de novo co-assembly of bacterial genomes from multiple single cells outperforms single cell assembly of each individual one in all standard metrics. Moreover, co-assembly outperforms mixed assembly in which the input datasets are simply concatenated. We implemented our algorithm in a software tool called HyDA which is available from http://compbio.cs.wayne.edu/software/hyda.