15、诺禾培训班课程其他trinity拼接

Trinity—拼接转录调控—方彬彬20140813转录组分析流程基因组vs转录组近似的测序深度测双链NA基因组测序深度可能会有若干数量级的改变可以是链特异性的，因此转录组组装程序需要考虑利用链特异性信息来解析正义和反义转录本同一个基因的不同转录本会共享外显子转录组转录组拼接策略Mapping-firstapprochesMethod:firstalignallthereadstoareferencegenomeandthenmergesequenceswithoverlappingalignmentTools:Scripture,Cufflinksmaximumsensitivity,butdependoncorrectread-to-referencealignment,thereferencegenomeisavailableAssembly-firstapprochesTools:Trinitydonotrequireanyread-referencealignments,importantwhenthegenomicsequenceisnotavailable,isgapped,highlyfragmentedorsubstantiallyaltered,asincancercellsIntroductionTrinity,developedattheBroadInstituteandtheHebrewUniversityofJerusalem(耶路撒冷希伯莱大学),representsanovelmethodfortheefficientandrobustdenovoreconstrucionoftranscriptomesfromRNA-seqdataTrinitycombinesthreeindependentsoftwaremodules:Inchworm,Chrysalis,andButterfly,appliedsequentiallytoprecesslargevolumesofRNA-seqreads.ps:Broad,一个附属于MIT和harvard的，在生物医学和基因组学研究领域神一样存在的机构 Inchworm1.分解测序reads，构建k-mer字典(k=25)k-mer“25-mersworkverywellforbothhighlyandlowlyexpressedtranscripts”deBruijngraph字典kmer[sequence]=coverage--seqTypefq--JM(JellyfishMemory)(~1GRAMper1Mpairsofreads)2.从k-mer字典中移除error-containingk-merk-mersthathaveidenticalk-1prefixes,differingonlyattheirterminalnumleotide,andremovingthosek-mersthatare<5%abundantascomparedtothemosthighlyabundantk-merofthegrouperror-containingkmerswillbegreatlyenrichedwithinthelowabundancekmercountsandcanbeexcludedwithminimalloss--min_kmer_cov23.选择seedk-mer标准：1.coverage最高；2.高复杂性；3.在read中至少出现2次；4.无回文序列4.Seedk-mer延伸contig每一次从k-mer字典中找到一个跟前一个kmer有k-1个overlap并且丰度最高的kmer，延伸1个base。一直迭代到没有符合条件的kmer,每使用一个kmer，将其从kmer字典中移除thesequenceyieldedfromthebidirectionalseedk-merextensionisreportedasadrafttranscriptcontig5.重复seedselection和bidirectionalk-merextension直到k-mer字典耗尽6.过滤contigWithanaveragek-mercoverageof2Lengthatleast48(2*(k-1))Inchworm1.分解测序reads，构建k-mer字典(k=25)2.从k-mer字典中移除error-containingk-mer3.选择seedk-mer4.Seedk-mer延伸contig5.重复seedselection和bidirectionalk-merextension直到k-mer字典耗尽6.过滤contigInchwormdoesaverygoodjobatreconstructingtranscriptsfromRNA-seqdata,butsinceitleveragesonlyuniquek-mersforcontigconstruction,itcanonlyreportthepartsofalternativelysplicedisoformsthatareunique.SubsequentTrinitystepsreconstructthefulllengthalternativelysplicedtranscripts. Chrysalis由于contig的构造方法，使得各个contig之间不可能共享k个以上序列，因此这些Inchwormcontigs不能很好的表征各种可变剪切形式和同源基因等情况，Chrysalis将那些有重叠的contigs聚类，构成components，component就成为一组可变剪切isoform或同源基因可能的表征的集合。1.Groupscontigsintoconnectedcomponentscommonk-1basesperfectoverlap;Readsupport:therearenreadsthatspanacrossapotentialjunction(welds)andextendperfectmatchesby(k-1)/2basesoneachside;--min_glue(default:2)2.BuildadeBruijngraphforeachcomponentK-1mer→nodeKmer→edge3.ReadsassignmentThereadsarethenmappedtocomponentsbyselectingthecomponentthatsharesthemostk-1-merswiththeread.Chrysalisalsocountsallk-mers(inassignedreads)andstoresthemas'edgeweight'(fordeBruijnconstructedinlaststep)toindicatetheirsupportinthereadset.4.FilterComponentswithlessthanaminimumnumberofnodesarediscardedChrysalis1.groupscontigsintoconnectedcomponents2.BuildadeBruijngraphforeachcomponent3.Readsassignment4.FilterButterflyGraphsimplificationMergingconsecutivenodesinlinearpathsinthedeBruijngraphtoformnodesthatrepresentlongersequencesPruningedgesthatrepresentminordeviations(supportedbycomparativelyfewreads),whichlikelycorrespondtosequencingerrorsPathcallingTracesthepathsthatreadsandpairsofreadstakewithinthegraphandreportsthemostprobabletranscriptsasafastafile. ButterflyresolvesalternativelysplicedandparalogoustranscriptsSummary其他参数--jaccard_clipIfdataarederivedfromagene-densecompactgenome,suchasfromfungalgenomes,wheretranscriptsmayoftenoverlapinUTRregions.Trinitywillexaminetheconsistencyofreadpairingsandfragmenttranscriptsatpositionsthathavelittleread-pairingsupport.--SS_lib_type(Strand-specificlibrarytype)Pairedreads:RF:firstread(/1)offragmentpairissequencedasantisense(reverse(R)),andsecondread(/2)isinthesensestrand(forward(F));typicalofsequencingmethod.thedUTP/UDGFR:firstread(/1)offragmentpairissequencedassense(forward),andsecondread(/2)isintheantisensestrand(reverse)Unpaired(single)reads:F:thesinglereadisinthesense(forward)orientationR:thesinglereadisintheantisense(reverse)orientation一些参数 --jaccard_clip(setifyouhavepairedreads andyouexpecthighgenedensitywithUTR overlap) --min_contig_length(minimumassembled contiglengthtoreport) --min_glue(minnumberofreadsneededtogluetwoinchwormcontigstogether)其他问题>comp2_c0_seq1len=2364path=[0:0-587588:588-10761146:1077-2363]comp2:sequenceisderivedfromChrysaliscomponent#2c0:sequencealsocorrespondstoButterflyponent#0(duringgraphcompactionandpruning,somecomponentsarepartitionedintodisconnectedponents).seq1:sequencecountfromchrysaliscomponent2,butterflyponentzero.Ifthisponentyieldsmultiplesequences,thesewillhavedifferentseqnumbers.len:lengthofthetranscriptsequence单独拼接和混合拼接Thegeneralideaistocombineallyourrna-seqdataandgenerateoneassembly.Then,toalignthereadsfromthedifferentsamplesseparatelytotheTrinityassemblies,computingabundanceestimatesbasedoneachreadset.Finally,youdothedifferentialexpressionanalysistoidentifythoseTrinityassembliesthatareofinterest.Thisisalloutlinedinthedownstreamanalysissectionofthedocumentation.--BrianJ.HaasN50/N90：按照长度将拼接转录本从大到小排序，累加转录本的长度，到不小于总长50%/90%的拼接转录本的长度就是N50/N90。2023/1/10其他问题拼接参数回顾纯分析参数：--seqTypefq--JM200G--SS_lib_typeRF--min_kmer_cov2--min_glue2--CPU10Trinity.fasta文件、unigene.fasta文件回顾测序深度可能会有若干数量级的改变可以是链特异性的，因此转录组组装程序需要考虑利用链特异性信息来解析正义和反义转录本同一个基因的不同转录本会共享外显子转录组TRINITY如何解决转录组拼接的难题？？？Practice1.Whatcomputingresourcesarerequired?Ideally,youwillhaveaccesstoalarge-memoryserver,having~1GofRAMper1Mreadstobeassembled(butoften,muchlessmemorymay