2022
A curated collection of human vaccination response signatures
Smith K, Chawla D, Dhillon B, Ji Z, Vita R, van der Leest E, Weng J, Tang E, Abid A, Peters B, Hancock R, Floratos A, Kleinstein S. A curated collection of human vaccination response signatures. Scientific Data 2022, 9: 678. PMID: 36347894, PMCID: PMC9643367, DOI: 10.1038/s41597-022-01558-1.Peer-Reviewed Original Research
2019
Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE)
Meng H, Yaari G, Bolen CR, Avey S, Kleinstein SH. Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE). PLOS Computational Biology 2019, 15: e1006899. PMID: 30939133, PMCID: PMC6461294, DOI: 10.1371/journal.pcbi.1006899.Peer-Reviewed Original Research
2018
The CAIRR Pipeline for Submitting Standards-Compliant B and T Cell Receptor Repertoire Sequencing Studies to the National Center for Biotechnology Information Repositories
Bukhari SAC, O’Connor M, Martínez-Romero M, Egyedi AL, Willrett D, Graybeal J, Musen MA, Rubelt F, Cheung KH, Kleinstein SH. The CAIRR Pipeline for Submitting Standards-Compliant B and T Cell Receptor Repertoire Sequencing Studies to the National Center for Biotechnology Information Repositories. Frontiers In Immunology 2018, 9: 1877. PMID: 30166985, PMCID: PMC6105692, DOI: 10.3389/fimmu.2018.01877.Peer-Reviewed Original ResearchConceptsMetadata qualityInformation repositoryAdaptive immune receptor repertoiresLarge-scale dataWeb–based templateSoftware frameworkData annotationData standardsEffective sharingAIRR-seq dataReceptor repertoireData submittersCell receptorSequence filesAdaptive immune responsesRepositoryImmune receptor repertoiresMetadataData setsT cell receptorArchive databaseB cell receptorCEDAR OnDemand: a browser extension to generate ontology-based scientific metadata
Bukhari SAC, Martínez-Romero M, O’ Connor M, Egyedi AL, Willrett D, Graybeal J, Musen MA, Cheung KH, Kleinstein SH. CEDAR OnDemand: a browser extension to generate ontology-based scientific metadata. BMC Bioinformatics 2018, 19: 268. PMID: 30012108, PMCID: PMC6048706, DOI: 10.1186/s12859-018-2247-6.Peer-Reviewed Original ResearchConceptsMetadata entriesBrowser extensionWeb formsData repositoryOntology-based metadataWeb page contentBiomedical data repositoriesWeb-based interfacePage contentPublic data repositoriesRelevant ontologiesHTML formatSource datasetIndividual repositoriesNCBO BioPortalCollected metadataExperimental metadataScientific metadataMetadataOndemandPre-defined listOntologyRepositoryInput fieldDatasetA spectral clustering-based method for identifying clones from high-throughput B cell repertoire sequencing data
Nouri N, Kleinstein SH. A spectral clustering-based method for identifying clones from high-throughput B cell repertoire sequencing data. Bioinformatics 2018, 34: i341-i349. PMID: 29949968, PMCID: PMC6022594, DOI: 10.1093/bioinformatics/bty235.Peer-Reviewed Original Research
2016
VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements
Toby IT, Levin MK, Salinas EA, Christley S, Bhattacharya S, Breden F, Buntzman A, Corrie B, Fonner J, Gupta NT, Hershberg U, Marthandan N, Rosenfeld A, Rounds W, Rubelt F, Scarborough W, Scott JK, Uduman M, Vander Heiden JA, Scheuermann RH, Monson N, Kleinstein SH, Cowell LG. VDJML: a file format with tools for capturing the results of inferring immune receptor rearrangements. BMC Bioinformatics 2016, 17: 333. PMID: 27766961, PMCID: PMC5073965, DOI: 10.1186/s12859-016-1214-3.Peer-Reviewed Original Research
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 methodsAllelesHypermutationAutomated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles
Gadala-Maria D, Yaari G, Uduman M, Kleinstein SH. Automated analysis of high-throughput B-cell sequencing data reveals a high frequency of novel immunoglobulin V gene segment alleles. Proceedings Of The National Academy Of Sciences Of The United States Of America 2015, 112: e862-e870. PMID: 25675496, PMCID: PMC4345584, DOI: 10.1073/pnas.1417683112.Peer-Reviewed Original Research
2014
pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires
Vander Heiden JA, Yaari G, Uduman M, Stern JN, O'Connor KC, Hafler DA, Vigneault F, Kleinstein SH. pRESTO: a toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires. Bioinformatics 2014, 30: 1930-1932. PMID: 24618469, PMCID: PMC4071206, DOI: 10.1093/bioinformatics/btu138.Peer-Reviewed Original Research
2013
Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection
Zaslavsky E, Nudelman G, Marquez S, Hershberg U, Hartmann BM, Thakar J, Sealfon SC, Kleinstein SH. Reconstruction of regulatory networks through temporal enrichment profiling and its application to H1N1 influenza viral infection. BMC Bioinformatics 2013, 14: s1. PMID: 23734902, PMCID: PMC3633009, DOI: 10.1186/1471-2105-14-s6-s1.Peer-Reviewed Original ResearchConceptsRegulatory networksTranscription factorsExtensive genetic reprogrammingUnderlying transcriptional networksGene expression patternsAntiviral responseGene expression changesNovel antiviral factorTranscriptional cascadeTranscriptional networksDendritic cellsPromoter analysisRegulatory connectionsGenetic reprogrammingTranscriptional programsExpression patternsNetwork reconstruction methodsExpression changesCellular responsesExpression kineticsMonocyte-derived human dendritic cellsAntiviral stateHuman monocyte-derived dendritic cellsSuch virus infectionsImmune antagonists
2011
Detecting selection in immunoglobulin sequences
Uduman M, Yaari G, Hershberg U, Stern JA, Shlomchik MJ, Kleinstein SH. Detecting selection in immunoglobulin sequences. Nucleic Acids Research 2011, 39: w499-w504. PMID: 21665923, PMCID: PMC3125793, DOI: 10.1093/nar/gkr413.Peer-Reviewed Original Research