2015
The mutation patterns in B-cell immunoglobulin receptors reflect the influence of selection acting at multiple time-scales
Yaari G, Benichou JI, Vander Heiden J, Kleinstein SH, Louzoun Y. The mutation patterns in B-cell immunoglobulin receptors reflect the influence of selection acting at multiple time-scales. Philosophical Transactions Of The Royal Society B Biological Sciences 2015, 370: 20140242. PMID: 26194756, PMCID: PMC4528419, DOI: 10.1098/rstb.2014.0242.Peer-Reviewed Original ResearchMeSH KeywordsAntibody AffinityAntibody DiversityB-LymphocytesCell LineageClonal Selection, Antigen-MediatedComplementarity Determining RegionsGenes, ImmunoglobulinHumansImmunoglobulin Heavy ChainsImmunoglobulin Variable RegionModels, GeneticModels, ImmunologicalMutationReceptors, Antigen, B-CellSomatic Hypermutation, ImmunoglobulinTime FactorsConceptsLineage treesPositive selectionStrong selection pressureLong-term selectionInfluence of selectionGene familyVariable gene familiesComplementarity determining regionsClone membersMutation patternsSelection pressureB cell populationsImmunoglobulin genesB cellsFramework regionsSomatic hypermutationSomatic mutationsAffinity maturationMutationsClone sizeMaturation processLong trunkAffinity maturation processSignificant diversityMultiple roundsChange-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data
Gupta NT, Vander Heiden JA, Uduman M, Gadala-Maria D, Yaari G, Kleinstein SH. Change-O: a toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data. Bioinformatics 2015, 31: 3356-3358. PMID: 26069265, PMCID: PMC4793929, DOI: 10.1093/bioinformatics/btv359.Peer-Reviewed Original ResearchConceptsHigh-throughput sequencing technologyB cell immunoglobulinLarge-scale characterizationLineage treesSpecialized computational methodsSelection pressureSequencing technologiesSomatic diversityClonal populationsIg repertoireSomatic hypermutationIg sequencesDiversityNon-commercial useSuite of utilitiesRepertoire diversityGermlineComputational methodsAllelesHypermutation
2014
Integrating B Cell Lineage Information into Statistical Tests for Detecting Selection in Ig Sequences
Uduman M, Shlomchik MJ, Vigneault F, Church GM, Kleinstein SH. Integrating B Cell Lineage Information into Statistical Tests for Detecting Selection in Ig Sequences. The Journal Of Immunology 2014, 192: 867-874. PMID: 24376267, PMCID: PMC4363135, DOI: 10.4049/jimmunol.1301551.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsAntibody AffinityAntibody DiversityB-Lymphocyte SubsetsCell LineageClonal Selection, Antigen-MediatedComputer SimulationConfounding Factors, EpidemiologicGene Rearrangement, B-LymphocyteGenes, ImmunoglobulinHumansMiceModels, ImmunologicalModels, StatisticalROC CurveSequence Analysis, DNASomatic Hypermutation, ImmunoglobulinVDJ ExonsConceptsLineage treesHigh-throughput sequencing technologyLineage tree shapesCell lineage informationIg sequencesRatio of replacementTree-shape analysisStatistical frameworkSequence-based methodsBinomial statistical analysisExperimental data setsIndicators of selectionSequencing technologiesLineage informationSequencing depthNumber of generationsData setsHybrid methodVivo selectionSilent mutationsTree shapeStatistical testsSequenceShape analysisMutations
2006
Mutation parameters from DNA sequence data using graph theoretic measures on lineage trees
Magori-Cohen R, Louzoun Y, Kleinstein SH. Mutation parameters from DNA sequence data using graph theoretic measures on lineage trees. Bioinformatics 2006, 22: e332-e340. PMID: 16873490, DOI: 10.1093/bioinformatics/btl239.Peer-Reviewed Original ResearchConceptsLineage treesDNA sequencesDNA sequence dataSomatic hypermutationMaximum likelihood analysisTree shapeBioinformatics methodsSequence dataLethal mutationsMutation rateNumber of generationsLikelihood analysisMutation parametersB cellsSynthetic treeClonal expansionTreesSequenceMutationsHypermutationAffinity maturationCellsImportant linkClonesUnexpected locations