2023
mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation
Movassagh M, Schiff S, Paulson J. mbQTL: an R/Bioconductor package for microbial quantitative trait loci (QTL) estimation. Bioinformatics 2023, 39: btad565. PMID: 37707523, PMCID: PMC10516520, DOI: 10.1093/bioinformatics/btad565.Peer-Reviewed Original ResearchConceptsSingle nucleotide variationsRNA sequencingMicrobial abundance dataQuantitative trait lociSingle nucleotide polymorphism dataRibosomal RNA sequencingField of genomicsWhole-genome sequencingEvidence of interplayMutational profileTrait lociMicrobial communitiesMicrobial abundancePolymorphism dataMicrobial populationsGenome sequencingAbundance dataFirst R packageHuman geneticsBioconductor packageGenetic variantsMicrobiome dataSequencingR packageAbundance
2022
Differential richness inference for 16S rRNA marker gene surveys
Kumar M, Slud E, Hehnly C, Zhang L, Broach J, Irizarry R, Schiff S, Paulson J. Differential richness inference for 16S rRNA marker gene surveys. Genome Biology 2022, 23: 166. PMID: 35915508, PMCID: PMC9344657, DOI: 10.1186/s13059-022-02722-x.Peer-Reviewed Original ResearchConceptsMarker gene surveysRRNA marker gene surveysGene surveysMicrobial assemblagesSpecies discoveryMicrobial taxaMicrobial communitiesMicrobiome surveysRichness estimationSequencing readsDiversity measuresTaxaGenus abundanceMicrobiome dataR packageAbundanceRichnessDiscoveryDiversityReadsAssemblagesObserved numberExperimental evidenceAccumulationInference
2021
Vaginal microbiome topic modeling of laboring Ugandan women with and without fever
Movassagh M, Bebell L, Burgoine K, Hehnly C, Zhang L, Moran K, Sheldon K, Sinnar S, Mbabazi-Kabachelor E, Kumbakumba E, Bazira J, Ochora M, Mulondo R, Nsubuga B, Weeks A, Gladstone M, Olupot-Olupot P, Ngonzi J, Roberts D, Meier F, Irizarry R, Broach J, Schiff S, Paulson J. Vaginal microbiome topic modeling of laboring Ugandan women with and without fever. Npj Biofilms And Microbiomes 2021, 7: 75. PMID: 34508087, PMCID: PMC8433417, DOI: 10.1038/s41522-021-00244-1.Peer-Reviewed Original ResearchMeSH KeywordsAdultBacteriaBiodiversityCluster AnalysisFemaleHumansLabor, ObstetricLactobacillusMicrobiotaPregnancyRNA, Ribosomal, 16SUgandaVaginaConceptsIntrapartum feverClinical variablesHigh prevalenceVaginal microbiomeUgandan womenLonger labour durationMaternal clinical featuresYoung maternal ageDuration of pregnancyOnset of laborMicrobial communitiesVaginal microbial communitiesAfebrile mothersFebrile mothersPeripartum courseMaternal feverNeonatal outcomesLabor durationClinical featuresMaternal ageVaginal microbesFeverOutcome riskVeillonella genusMicrobiome influences
2011
Association of bacteria with hydrocephalus in Ugandan infants.
Li L, Padhi A, Ranjeva S, Donaldson S, Warf B, Mugamba J, Johnson D, Opio Z, Jayarao B, Kapur V, Poss M, Schiff S. Association of bacteria with hydrocephalus in Ugandan infants. Journal Of Neurosurgery Pediatrics 2011, 7: 73-87. PMID: 21194290, DOI: 10.3171/2010.9.peds10162.Peer-Reviewed Original ResearchConceptsUgandan infantsNeonatal sepsisPostinfectious hydrocephalusMajority of patientsMost patientsRecent infectionPolymerase chain reactionEffective treatmentPatientsPrevention strategiesHydrocephalusInfectionInfantsAcinetobacter speciesChain reactionAssociation of bacteriaBacterial DNAGram-negative bacteriaNegative bacteriaSepsisEnvironmental samplingSyndromeSeason infection