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高通量测序数据识别拼接错误方法 Title:MethodsforIdentifyingSplicingErrorsinHighThroughputSequencingData Abstract: Highthroughputsequencingtechnologieshaverevolutionizedthestudyofgeneexpressionandsplicingevents.However,thisneweraofdatagenerationcomeswithitsownchallenges,oneofwhichistheidentificationofsplicingerrors.Splicingerrorscanariseduetovariousfactorssuchasmisalignment,sequencingerrors,orbiologicalvariations.Accuratedetectionoftheseerrorsiscrucialforthereliableanalysisofgeneexpressionandunderstandingcomplexbiologicalprocesses.Inthispaper,wereviewanddiscussseveralmethodsthathavebeendevelopedtoidentifysplicingerrorsinhighthroughputsequencingdata. Introduction: Highthroughputsequencingtechnologies,suchasRNA-Seq,havebecomepowerfultoolsforstudyinggeneexpressionandsplicingevents.Thesetechnologiesgeneratemassiveamountsofdata,providinguswithunprecedentedinsightsintotheintricaciesofcellularprocesses.However,theanalysisandinterpretationofthesedatacanbechallenging,especiallywhenitcomestoidentifyingsplicingerrors.Splicingerrors,alsoknownasalternativesplicingevents,canoccurduringtheprocessingofpre-mRNAintomaturemRNA,resultingintheproductionofaberranttranscripts.Theseerrorscanhavesignificantimpactsongeneexpressionandproteinfunction.Therefore,accurateidentificationofsplicingerrorsisessentialforunderstandingtheunderlyingbiologyandpotentialdiseasemechanisms. MethodsforIdentifyingSplicingErrors: 1.Alignment-basedMethods: Alignment-basedmethodsarewidelyusedformappingsequencedreadstoareferencegenomeortranscriptome.ThesemethodstypicallyusealgorithmssuchasBurrows-WheelerTransform(BWT)orhashtablestoalignreads.However,splicingerrorscanleadtomisalignmentofreads,resultingininaccuratemapping.Toaddressthischallenge,severalalignment-basedmethodsintegratesplicing-awarealgorithms,suchasTopHatandSTAR,whichtakeintoaccountsplicejunctionswhilealigningreads.Thesemethodsimprovetheaccuracyofreadalignmentandenablethedetectionofsplicingerrors. 2.ReadCoverageAnalysis: Splicingerrorscanresultinchangesinreadcoverageacro