2015
Change-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