PSE-HMM: genome-wide CNV detection from NGS data using an HMM with Position-Specific Emission probabilities

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• 作者：Seyed Amir Malekpour ; Hamid Pezeshk ; Mehdi Sadeghi
• 关键词：Next Generation Sequencing (NGS) ; Hidden Markov Models (HMMs) ; Expectation Maximization (EM) algorithm ; mixture densities ; Copy Number Variation (CNV)
• 刊名：BMC Bioinformatics
• 出版年：2017
• 出版时间：December 2017
• 年：2017
• 卷：18
• 期：1
• 全文大小：781KB
• 刊物主题：Bioinformatics; Microarrays; Computational Biology/Bioinformatics; Computer Appl. in Life Sciences; Algorithms;
• 出版者：BioMed Central
• ISSN：1471-2105
• 卷排序：18

文摘

BackgroundCopy Number Variation (CNV) is envisaged to be a major source of large structural variations in the human genome. In recent years, many studies apply Next Generation Sequencing (NGS) data for the CNV detection. However, still there is a necessity to invent more accurate computational tools.