基于二代测序的基因组缺失变异综合检测策略

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1、北京化工大学硕士学位论文detectionsensitivity,doesinitialmappingandfollowingsplitreadalignmentofpaired--endreadstoidentifyacomprehensivesetoflbp·-resolutiondeletioncandidates．Thesecondstep，aimingatminimizingfalsediscoveryrate，extractsdeletion-relatedfeaturesbymakingfulluseofthetwicealignmentresultsaccordin

2、gtothefundamentalsofread—depthmethods，split—readapproachesandread-pairtechnologies，andthenusesadiscriminativemodelwithhighgeneralizationabilitytodistinguishtruefromfalsedeletioncandidatesbasedonthefeatures．Theexperimentalresultsshowthatcomparedwiththetraditionalsplit—readapproaches，theintegrat

3、edstrategynotonlydetectsdeletionsdowntosingle··base·-pairlevelbutalsoeffectivelyreducesthenumberoffalsepositiveswithnegligiblelossofsensitivity．(3)Studiedtheapplicabilityofsupportvectormachineandrandomforesttotheproposedstrategy,andfurtheranalyzedthecontributionsofeachfeaturetoadeletionpredict

4、ion．Theexperimentalresultsshowthatbytakingamachinelearningmodelwithwellgeneralizationperformanceasthediscriminativemodeloftheproposedstrategy,itcaneffectivelyreducefalsepositivecallswithnegligiblelossofsensitivity．Moreover,thestudyoffeatureimportancefindsthattheinfluenceofeachfeatureonthemodel

5、predictionaccuracychangeswithreaddepthofcoverage．KEYWORDS：next．generationsequencing(NGS)，deletion，featureextraction，machinelearningalgorithmsIV目录第一章绪论⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯11．1课题背景和研究意义⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯．．11．2基于测序的结构变异检测研究现状⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯·21．2．1聚簇法⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯

6、21．2．2概率分布法⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯··41．2．3机器学习法⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯··51．2，4混合法⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯61．3课题主要研究内容⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯··71．4本文结构⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯··8第二章缺失变异检测环境的研究⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯92．1引言⋯⋯⋯⋯⋯⋯⋯⋯·2．2缺失变异标准集的生成·2．3个体基因组序列的仿真·2．4配对末端测序的模拟⋯·2．4．

7、1配对末端测序⋯⋯⋯·2．4．2测序序列的映射⋯⋯·2．5本章小结⋯⋯⋯⋯⋯⋯·第三章基于AdaBoost的缺失变异综合检测策略⋯⋯⋯⋯⋯⋯⋯⋯⋯193．1引言⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯193．2特征的提取⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯193．2．1序列对映射距离⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯203。2。2分裂比对⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯⋯·213．