2013
Models of Somatic Hypermutation Targeting and Substitution Based on Synonymous Mutations from High-Throughput Immunoglobulin Sequencing Data
Yaari G, Vander Heiden J, Uduman M, Gadala-Maria D, Gupta N, Stern JN, O’Connor K, Hafler DA, Laserson U, Vigneault F, Kleinstein SH. Models of Somatic Hypermutation Targeting and Substitution Based on Synonymous Mutations from High-Throughput Immunoglobulin Sequencing Data. Frontiers In Immunology 2013, 4: 358. PMID: 24298272, PMCID: PMC3828525, DOI: 10.3389/fimmu.2013.00358.Peer-Reviewed Original ResearchAccurate background modelSynonymous mutationsNon-coding regionsParticular codon usageNon-functional sequencesComputational analysis methodsObserved mutation patternExisting modelsBackground modelInfluence of selectionCodon usageSHM targetingBase compositionImproved modelSequencing dataNucleotide substitutionsAnalysis methodStatistical analysisFunctional sequencesMutation targetingB-cell cancersModelSomatic hypermutation patternsMutationsHypermutation patterns
2012
Quantifying selection in high-throughput Immunoglobulin sequencing data sets
Yaari G, Uduman M, Kleinstein SH. Quantifying selection in high-throughput Immunoglobulin sequencing data sets. Nucleic Acids Research 2012, 40: e134-e134. PMID: 22641856, PMCID: PMC3458526, DOI: 10.1093/nar/gks457.Peer-Reviewed Original ResearchConceptsQuantifying selectionDifferent selection pressuresHigh-throughput immunoglobulinSomatic hypermutationNext-generation sequencing dataDNA mutation patternsSomatic mutation patternsGroups of sequencesAntigen-driven selection processMutation patternsSequence dataSelection pressureSequencing dataB cell affinity maturationB-cell cancersNegative selection