Featured Publications
SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data
Liu Y, Li N, Qi J, Xu G, Zhao J, Wang N, Huang X, Jiang W, Wei H, Justet A, Adams T, Homer R, Amei A, Rosas I, Kaminski N, Wang Z, Yan X. SDePER: a hybrid machine learning and regression method for cell-type deconvolution of spatial barcoding-based transcriptomic data. Genome Biology 2024, 25: 271. PMID: 39402626, PMCID: PMC11475911, DOI: 10.1186/s13059-024-03416-2.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsGene Expression ProfilingHumansMachine LearningRegression AnalysisRNA-SeqSequence Analysis, RNASingle-Cell AnalysisSoftwareTranscriptomeiDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects
Liu Y, Zhao J, Adams T, Wang N, Schupp J, Wu W, McDonough J, Chupp G, Kaminski N, Wang Z, Yan X. iDESC: identifying differential expression in single-cell RNA sequencing data with multiple subjects. BMC Bioinformatics 2023, 24: 318. PMID: 37608264, PMCID: PMC10463720, DOI: 10.1186/s12859-023-05432-8.Peer-Reviewed Original ResearchG2S3: A gene graph-based imputation method for single-cell RNA sequencing data
Wu W, Liu Y, Dai Q, Yan X, Wang Z. G2S3: A gene graph-based imputation method for single-cell RNA sequencing data. PLOS Computational Biology 2021, 17: e1009029. PMID: 34003861, PMCID: PMC8189489, DOI: 10.1371/journal.pcbi.1009029.Peer-Reviewed Original ResearchMeSH KeywordsComputational BiologyDatasets as TopicGene Expression ProfilingHumansSequence Analysis, RNASingle-Cell AnalysisConceptsSingle-cell transcriptomic datasetsTranscriptomic datasetsGene expressionSingle-cell RNA sequencing technologySingle-cell transcriptomic studiesSingle-cell RNA sequencing dataRNA sequencing technologyRNA sequencing dataSingle-cell resolutionGene expression profilesAdjacent genesTranscriptomic studiesSequencing technologiesSequencing dataExpression profilesGene graphDownstream analysisGenesCell trajectoriesDropout eventsCell subtypesExpressionHigh data sparsityCells
2023
A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy
Deng W, Li B, Wang J, Jiang W, Yan X, Li N, Vukmirovic M, Kaminski N, Wang J, Zhao H. A novel Bayesian framework for harmonizing information across tissues and studies to increase cell type deconvolution accuracy. Briefings In Bioinformatics 2023, 24: bbac616. PMID: 36631398, PMCID: PMC9851324, DOI: 10.1093/bib/bbac616.Peer-Reviewed Original Research
2020
Approaches for integrating heterogeneous RNA-seq data reveal cross-talk between microbes and genes in asthmatic patients
Spakowicz D, Lou S, Barron B, Gomez JL, Li T, Liu Q, Grant N, Yan X, Hoyd R, Weinstock G, Chupp GL, Gerstein M. Approaches for integrating heterogeneous RNA-seq data reveal cross-talk between microbes and genes in asthmatic patients. Genome Biology 2020, 21: 150. PMID: 32571363, PMCID: PMC7310008, DOI: 10.1186/s13059-020-02033-z.Peer-Reviewed Original ResearchMeSH KeywordsAsthmaCase-Control StudiesComputational BiologyFemaleHumansMaleMicrobiotaMiddle AgedSequence Analysis, RNASputumUnsupervised Machine Learning
2017
Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis
Vukmirovic M, Herazo-Maya JD, Blackmon J, Skodric-Trifunovic V, Jovanovic D, Pavlovic S, Stojsic J, Zeljkovic V, Yan X, Homer R, Stefanovic B, Kaminski N. Identification and validation of differentially expressed transcripts by RNA-sequencing of formalin-fixed, paraffin-embedded (FFPE) lung tissue from patients with Idiopathic Pulmonary Fibrosis. BMC Pulmonary Medicine 2017, 17: 15. PMID: 28081703, PMCID: PMC5228096, DOI: 10.1186/s12890-016-0356-4.Peer-Reviewed Original ResearchConceptsPaired-end sequencingTranscript profilingHuman genomeRNA sequencingTranscriptomic profilingFFPE lung tissuesSequencing readsLung tissueTotal RNABackgroundIdiopathic pulmonary fibrosisLethal lung diseaseSequencingReadsProfilingPulmonary fibrosisLung diseaseUnknown etiologyIPF tissueGenomeHiSeqTissueTopHat2GenesIPFRNA
2012
Modeling RNA degradation for RNA-Seq with applications
Wan L, Yan X, Chen T, Sun F. Modeling RNA degradation for RNA-Seq with applications. Biostatistics 2012, 13: 734-747. PMID: 22353193, PMCID: PMC3616752, DOI: 10.1093/biostatistics/kxs001.Peer-Reviewed Original Research