Featured Publications
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
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
GameRank: R package for feature selection and construction
Henneges C, Paulson J. GameRank: R package for feature selection and construction. Bioinformatics 2022, 38: 4840-4842. PMID: 35951761, PMCID: PMC9563696, DOI: 10.1093/bioinformatics/btac552.Peer-Reviewed Original Research
2020
MicrobiomeExplorer: an R package for the analysis and visualization of microbial communities
Reeder J, Huang M, Kaminker J, Paulson J. MicrobiomeExplorer: an R package for the analysis and visualization of microbial communities. Bioinformatics 2020, 37: 1317-1318. PMID: 32960962, PMCID: PMC8193707, DOI: 10.1093/bioinformatics/btaa838.Peer-Reviewed Original Research
2019
metagenomeFeatures: an R package for working with 16S rRNA reference databases and marker-gene survey feature data
Olson N, Shah N, Kancherla J, Wagner J, Paulson J, Bravo H. metagenomeFeatures: an R package for working with 16S rRNA reference databases and marker-gene survey feature data. Bioinformatics 2019, 35: 3870-3872. PMID: 30821316, PMCID: PMC6761971, DOI: 10.1093/bioinformatics/btz136.Peer-Reviewed Original Research
2017
Tissue-aware RNA-Seq processing and normalization for heterogeneous and sparse data
Paulson J, Chen C, Lopes-Ramos C, Kuijjer M, Platig J, Sonawane A, Fagny M, Glass K, Quackenbush J. Tissue-aware RNA-Seq processing and normalization for heterogeneous and sparse data. BMC Bioinformatics 2017, 18: 437. PMID: 28974199, PMCID: PMC5627434, DOI: 10.1186/s12859-017-1847-x.Peer-Reviewed Original ResearchConceptsRNA-seq data setsRNA-seqGenotype-Tissue ExpressionRNA-seq processingGenome-wide transcriptional profilingRNA-seq studiesRNA-seq dataGene filteringDownstream analysisRNA sequencingTranscriptional profilesDiverse tissuesAnalytical pipelineR packageQuality controlSignificant analytical challengeSoftware pipelineGenesRNAMulti-group studyNormalization stepAnalytical challengesResultsWeTissueExpressionEstimating gene regulatory networks with pandaR
Schlauch D, Paulson J, Young A, Glass K, Quackenbush J. Estimating gene regulatory networks with pandaR. Bioinformatics 2017, 33: 2232-2234. PMID: 28334344, PMCID: PMC5870629, DOI: 10.1093/bioinformatics/btx139.Peer-Reviewed Original Research