A Statistical Approach Designed for Finding Mathematically Defined Repeats in Shotgun Data and Determining the Length Distribution of Clone

摘要 Thelargeamountofrepeats,especiallyhighcopyrepeats,inthegenomesofhigheranimalsandplantsmakeswholegenomeassembly(WGA)quitedifficult.Inordertosolvethisproblem,wetriedtoidentifyrepeatsandmaskthempriortoassemblyevenatthestageofgenomesurvey.Itisknownthatrepeatsofdifferentcopynumberhavedifferentprobabilitiesofappearanceinshotgundata,sobasedonthisprinciple,weconstructedastatisticalmodelandinferredcriteriaformathematicallydefinedrepeats(MDRs)atdifferentshotguncoverages.Accordingtothesecriteria,wedevelopedsoftwareMDRmaskertoidentifyandmaskMDRsinshotgundata.Withrepeatsmaskedpriortoassembly,thespeedofassemblywasincreasedwithlowererrorprobability.Inaddition,clone-insertsizeaffectstheaccuracyofrepeatassemblyandscaffoldconstruction.Wealsodesignedlengthdistributionofclone-insertsusingourmodel.Inoursimulatedgenomesofhumanandrice,thelengthdistributionofrepeatsisdifferent,sotheiroptimallengthdistributionsofclone-insertswerenotthesame.Thuswithoptimallengthdistributionofclone-inserts,agivengenomecouldbeassembledbetteratlowercoverage.

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A Statistical Approach Designed for Finding Mathematically Defined Repeats in Shotgun Data and Determining the Length Distribution of Clone—Inserts

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A Statistical Approach Designed for Finding Mathematically Defined Repeats in Shotgun Data and Determining the Length Distribution of Clone—Inserts

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