2024
nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework.
Gabernet G, Marquez S, Bjornson R, Peltzer A, Meng H, Aron E, Lee N, Jensen C, Ladd D, Polster M, Hanssen F, Heumos S, Yaari G, Kowarik M, Nahnsen S, Kleinstein S. nf-core/airrflow: An adaptive immune receptor repertoire analysis workflow employing the Immcantation framework. PLOS Computational Biology 2024, 20: e1012265. PMID: 39058741, DOI: 10.1371/journal.pcbi.1012265.Peer-Reviewed Original ResearchImmcantation frameworkAIRR-seqAIRR-seq dataAdaptive immune receptor repertoire sequencingSingle-cell sequencing datasetsClonal inferenceSequencing errorsSequencing datasetsNextflow workflowClonal relationshipReceptor sequencesRepertoire sequencingHigh-throughput processingSequenceImmune challengeAnalysis workflowT-cell receptor sequencingNextflowB cellsSARS-CoV-2Experimental toolResponse to SARS-CoV-2Infectious diseasesInferring B Cell Phylogenies from Paired H and L Chain BCR Sequences with Dowser.
Jensen C, Sumner J, Kleinstein S, Hoehn K. Inferring B Cell Phylogenies from Paired H and L Chain BCR Sequences with Dowser. The Journal Of Immunology 2024, 212: 1579-1588. PMID: 38557795, PMCID: PMC11073909, DOI: 10.4049/jimmunol.2300851.Peer-Reviewed Original ResearchConceptsPhylogenetic treeL chainsBranch lengthsBCR sequencesTree-building methodsSingle-cell sequencing dataHistory of mutationsSingle-cell sequencingPhylogenetic methodsSequence dataSequencing technologiesL chain sequencesTree accuracyEvolutionary processSingle-cellPhylogenyImmune responseSomatic hypermutationSequenceClonesMutationsB cell clonesHuman immune responseTreesBCR
2015
A model of somatic hypermutation targeting in mice based on high-throughput immunoglobulin sequencing data (TECH2P.910)
Cui A, Diniro R, Briggs A, Adams K, Vander Heiden J, O'Connor K, Vigneault F, Shlomchik M, Kleinstein S. A model of somatic hypermutation targeting in mice based on high-throughput immunoglobulin sequencing data (TECH2P.910). The Journal Of Immunology 2015, 194: 206.20-206.20. DOI: 10.4049/jimmunol.194.supp.206.20.Peer-Reviewed Original ResearchSimilar biological processesNon-functional sequencesObserved mutation patternDNA repair activityMutation patternsDNA motifsNext-generation sequencingHigh mutation frequencyUnselected mutationsSelection pressureSequencing dataBiological processesFunctional sequencesImmunoglobulin genesRepair activitySomatic hypermutation patternsSomatic hypermutationHypermutation patternsMutation frequencyIg sequencesT transitionSequenceHeavy chain transgenic miceMotifTransgenic mice
2012
Quantifying selection in high-throughput Immunoglobulin sequencing datasets (58.4)
Yaari G, Uduman M, Kleinstein S. Quantifying selection in high-throughput Immunoglobulin sequencing datasets (58.4). The Journal Of Immunology 2012, 188: 58.4-58.4. DOI: 10.4049/jimmunol.188.supp.58.4.Peer-Reviewed Original Research