Algorithm to Identify Frequent Coupled Modules(0001)

Algorithm to Identify Frequent Coupled Modules(0001)

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时间:2019-08-16

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1、AlgorithmtoIdentifyFrequentCoupledModulesfromTwo-LayeredNetworkSeriesPresentation:YangLiBackground:Background:�Currentnetworkanalysismethodsallfocusononeormultiplenetworksofthesametype.�Cellsareorganizedbymulti-layernetworks.�Differentkindsofnetworksinfluenceeachother.�RNA-se

2、qhasprovidedabundantmulti-levelprofilingdata------expressiondata&splicingdata.�Splicingcoupleswithtranscriptionwiththefollowingthreesplicingreactions------capping,splicing,cleavageandpolyadenylation.CouplednetworkCouplednetworkEssentialsEssentials:•RNA-seqdatasetsselection,pr

3、ocessingandnetworkconstruction•Non-uniformsamplingforfastcomputation•Formulatetheproblemasatenser-based0-1nonlinearintegerprogrammingmodel•Relaxthe0-1nonlinearintegerprogrammingintoacontinuouscomputationalproblem•OptimizationalgorithmandpatternextractionRNA-seqdatasetsselecti

4、on:RNA-seqdatasetsselection:�Database:NCBI’sSequenceReadArchive(SRA)�Criterions:allhumanRNA-seqdatasets,eachofwhichcontainsatleastsixsamples(38datasets)---------Theminimumvalueforrobustcorrelationestimationis6.Dataprocessing:Dataprocessing:①Foreachdataset,weusedtheTophattoolt

5、omapshortreadstothehg18referencegenome(reportonlytheoptimalalignmentanddiscardthosereadsthatmapequallywelltomultiplepositions).②WeappliedthetranscriptassemblytoolCufflinkstoestimateexpressionsforalltranscriptswithknownUCSCtranscriptionannotations.③Calculatedtheinclusionrateof

6、eachexonineverysample.Networkconstruction:Networkconstruction:�ForeachRNA-seqdatasetaweightedgeneco-expressionnetworkcanbeconstructed(edgesweightsarecorrelationsbetweentheexpressionprofilesoftwogenes).�Thesameprocedureisappliedtobuildaweightedexonco-splicingnetworkforthesameR

7、NA-seqdataset(edgeweightsrepresentcorrelationsbetweentheinclusionratesoftwoexons).Weightscomputation:Weightscomputation:①Computeleave-one-outPearsoncorrelationefficientr;②ComputeFisher'stransformationscoren−3⎛1+r⎞;z=ln⎜⎟2⎝1−r⎠①Standardizethez-scorestoenforcezeromeanandunitvar

8、iance;②Setvirtualsamplesizen'=10,andcompute⎛2⎞exp⎜z⎟−1⎝n'−3⎠.r'=⎛2⎞e

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