Aamna Lawrence, R. Shukla, Utkarsh Raj, Pritish Kumar Varadwaj
{"title":"利用NGS数据估计人类基因组表观遗传修饰的百分比","authors":"Aamna Lawrence, R. Shukla, Utkarsh Raj, Pritish Kumar Varadwaj","doi":"10.1109/BSB.2016.7552141","DOIUrl":null,"url":null,"abstract":"High Throughput Next Generation Sequencing (HT-NGS) technology has taken human and animal genome analysis and genomics researches to another level. From the analysis of the genomes by the aforementioned technologies, the most important modification to DNA, namely epigenetic modifications can be analyzed and studied to predict the gene expression and any disease onset in the future. By using the SRA (Serial Read Archive) toolkit, FastQC visualization tool and Bowtie aligner on ChIP-Seq (Chromatin Immunoprecipitation Sequenced) data, an estimate of the percentage epigenetic modifications or protein interactions found in the experimental human genome compared to those found normally in the genome of a healthy individual has been made. The results were used to predict whether the subject was at a risk of developing diseases due to mutations or epigenetic modifications like cancer.","PeriodicalId":363820,"journal":{"name":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating percentage epigenetic modifications in human genome using NGS data\",\"authors\":\"Aamna Lawrence, R. Shukla, Utkarsh Raj, Pritish Kumar Varadwaj\",\"doi\":\"10.1109/BSB.2016.7552141\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High Throughput Next Generation Sequencing (HT-NGS) technology has taken human and animal genome analysis and genomics researches to another level. From the analysis of the genomes by the aforementioned technologies, the most important modification to DNA, namely epigenetic modifications can be analyzed and studied to predict the gene expression and any disease onset in the future. By using the SRA (Serial Read Archive) toolkit, FastQC visualization tool and Bowtie aligner on ChIP-Seq (Chromatin Immunoprecipitation Sequenced) data, an estimate of the percentage epigenetic modifications or protein interactions found in the experimental human genome compared to those found normally in the genome of a healthy individual has been made. The results were used to predict whether the subject was at a risk of developing diseases due to mutations or epigenetic modifications like cancer.\",\"PeriodicalId\":363820,\"journal\":{\"name\":\"2016 International Conference on Bioinformatics and Systems Biology (BSB)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Bioinformatics and Systems Biology (BSB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BSB.2016.7552141\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Bioinformatics and Systems Biology (BSB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BSB.2016.7552141","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimating percentage epigenetic modifications in human genome using NGS data
High Throughput Next Generation Sequencing (HT-NGS) technology has taken human and animal genome analysis and genomics researches to another level. From the analysis of the genomes by the aforementioned technologies, the most important modification to DNA, namely epigenetic modifications can be analyzed and studied to predict the gene expression and any disease onset in the future. By using the SRA (Serial Read Archive) toolkit, FastQC visualization tool and Bowtie aligner on ChIP-Seq (Chromatin Immunoprecipitation Sequenced) data, an estimate of the percentage epigenetic modifications or protein interactions found in the experimental human genome compared to those found normally in the genome of a healthy individual has been made. The results were used to predict whether the subject was at a risk of developing diseases due to mutations or epigenetic modifications like cancer.