Bionumerics-生物信息分析软件应用简介

BioNumerics生物信息分析统一平台上海一贝科技许先生15821483715Onepowerfulplatformfordatabasing,analyzing,andsharingallyourbiologicaldataBioNumericsBioNumerics7.1模块Datamodules数据模块FingerprintData.Normalizationandanalysisofelectrophoresisfingerprintsfromslabgels,automatedsequencers,andlab-on-achipsystems.PreprocessingandanalysisofspectraldatasuchasMALDI.CharacterData.Importandanalyzecharacterdatafromawiderangeofsourcesincludingphenotypepanels,antibioticresistanceprofiles,microarrays,etc.SequenceData.AssembleandanalyzeSangersequencedataandNGSsequencereads.Accessawidevarietyofsequenceanalysis,searchandalignment,andcomparisontools.WholeGenomeMapData.Alignandclusterwholegenomemapsforbacterialstraintypingandidentification.TrendData.Analyzesequentialmeasurementsthatexpressanevolutionofoneparameterinfunctionofanother,e.g.,enzymaticactivity,growthcurves,rt-PCR,etc.AnalysismodulesTreeandNetworkInference.Selectfromanimpressiverangeofclusteringalgorithmstocalculateevolutionarytreesandrelationshipnetworks.Displayconfidencelevelsonclustersandbranches.DimensioningandMatrixMining.Createnon-hierarchicalgroupingsusingvariousordinationtechniquessuchasprincipalcomponentsanalysis,multidimensionalscaling,discriminantanalysis,andidentifydiscriminatingfeaturesbetweengroups.Performin-depthanalysisofcharactermatrices.GenomeAnalysisTools.Alignandcomparechromosomesside-by-sideorcalculatemultiplechromosomealignments.CalculateSNPsandmutationsonmulti-chromosomealignmentsandannotatenewchromosomes.Performmicrobialmetagenomicsdiversityanalysis.ClassifiersandIdentification.Identifyunknownsamplesagainstreferencedatasetsusingstate-of-the-artclassifierssuchasNaiveBayesian,SVM,ShrunkenCentroids,andarangeofsimilaritycoefficients.Enhanceyouridentificationprojectswithparameteroptimizationandcomprehensivecross-validationtools.Compareandvalidatedifferenttechniquesorprocedures.VersioningandAuditTrails.Createauditeddatabases(fullyFDATitle21CFRPart11compliant)byrecordingallchangesandkeepingallversionsofselecteddatabaseobjects.Compareandrestoreversions.Loguseractivity,createdigitalsigningprivileges.我们能存储什么？OrgnismField1:GenusField2:pecies信息字段字符数据AGCTCAAGCTGA序列定义多达80个信息字段链接外部数据库……表型特征抗菌敏感特征生化和形态特征微阵列（基因芯片）·········凝胶图像Sequencer图谱（e.g.AFLP）········DNA&核酸序列（e.g.16SrRNA）……指纹图谱我们能做什么？查询OrgnismField1:GenusField2:pecies亲缘分析•Usingfields•Usingexperiments•Usingrangesofvalues•Usinganycombinations•Multiplealignment•NeighborJoining•Parsimony•Maximunlikelihood•MANOVA(多元方差分析)•Discriminantannlysis•K-means,Jacknife•Significancetesting•PricipalComponentsAnalysis•Multi-Dim.Scaling•Self-OrganizingMaps•NeuralNetworks•UPGMA,NN,FN,Ward…•Standarddeviation•Copheneticcorrelation•Bootstrap•Libraryconstrution•Statisticalconfidence•NeuralNetworks数理统计聚类分析鉴定多维分析Bionumerics在疾控系统的主要应用MLST(多位点序列分析)实验和分析方法已经标准化，有国际数据库供查询和比对成功应用于全球、全国性暴发调查和菌型分布调查适合用于长期的、大范围的流行病学调查和监测菌群结构变化PFGE(脉冲场电泳)被广泛承认和使用的方法分辨能力优于MLST，分型结果与MLST有很高的一致性可以作为MLST实验菌株的初筛工具可以为暴发和聚集性病例调查提供实验室数据支持MLVA(多位点可变数目串联重复序列分型)在肠道菌和食源性疾病的暴发调查中已经被证实具有作用在呼吸道细菌中分型结果类似于MLST，分辨力高于PFGE和MLST需要寻找稳定的VNTR位点组合用于流行病学调查和菌群结构分析2003-2008年371株脑膜炎奈瑟菌MLST分析应用实例一：脑膜炎奈瑟菌种群结构分析和流行分布ST-4821型ST-4821型ST-7型ST-7型2003-2008年脑膜炎奈瑟菌主要序列群分布暴发相关菌株健康携带本底菌株健康携带本底菌株应用实例二：流脑暴发调查流脑菌株总携带率：28.3％暴发相关菌株携带率：15.7%应用实例三：肺炎克雷伯菌院内感染鉴别应用实例四：热带念珠菌种群结构分析ClusterIClusterII猪链球菌血清二型种群关系应用实例五：热带念珠菌种群结构分析应用实例六：MLVA数据MST分析•发现Cluster–分型数据提交–聚类分析–“VisualCheck”完全一致的分子分型特征应用实例七：发现各种Cluster应用实例八：分子流病应用•Pattern趋势长期监测:观察pattern的变化趋势是否一如既往的稳定•Pattern频率长期监测:观察pattern出现频率是否有较大变化应用实例九：归因分析•归因分析–引起食源性疾病的各种食品所占的比例（相对贡献）。DistanceandsimilaritymatricesCustomizeddisplayoftestpanelsCharacterimportfromatextfileoranExcelspreadsheet一代、二代测序应用RT-PCR/趋势类数据分析序列比对、序列拼接、同源性分析、酶切位点查找、引物设计、蛋白分析……序列分析全基因组数据分析物种分类和鉴定绘制图谱数据建库及共享ThanksforyourAttention