0000000000126278

AUTHOR

Caleb A. Lareau

showing 4 related works from this author

Single-cell trajectories reconstruction, exploration and mapping of omics data with STREAM

2019

Single-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data. We have tested STREAM on several synthetic and real datasets generated with different single-cell techno…

0301 basic medicineEpigenomicsMultifactor Dimensionality ReductionComputer scienceGeneral Physics and Astronomy02 engineering and technologyOmics dataMyoblastsMiceSingle-cell analysisGATA1 Transcription FactorMyeloid CellsLymphocyteslcsh:ScienceData processingMultidisciplinaryQGene Expression Regulation DevelopmentalRNA sequencingCell DifferentiationGenomics021001 nanoscience & nanotechnologyData processingDNA-Binding ProteinsInterferon Regulatory FactorsSingle-Cell Analysis0210 nano-technologyAlgorithmsOmics technologiesSignal TransductionLineage differentiationScienceComputational biologyGeneral Biochemistry Genetics and Molecular BiologyArticle03 medical and health sciencesErythroid CellsAnimalsCell LineageGeneral Chemistrydevelopmental trajectories visualizationHematopoietic Stem CellsPipeline (software)Visualization030104 developmental biologyTheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESCellular heterogeneitySingle cell analysilcsh:QGene expressionTranscriptomeTranscription FactorsNature Communications
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STREAM: Single-cell Trajectories Reconstruction, Exploration And Mapping of omics data

2018

AbstractSingle-cell transcriptomic assays have enabled the de novo reconstruction of lineage differentiation trajectories, along with the characterization of cellular heterogeneity and state transitions. Several methods have been developed for reconstructing developmental trajectories from single-cell transcriptomic data, but efforts on analyzing single-cell epigenomic data and on trajectory visualization remain limited. Here we present STREAM, an interactive pipeline capable of disentangling and visualizing complex branching trajectories from both single-cell transcriptomic and epigenomic data.

Omics dataCellular heterogeneityLineage differentiationComputer scienceGenomicsComputational biologyPipeline (software)Visualization
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Assessment of computational methods for the analysis of single-cell ATAC-seq data

2019

Abstract Background Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis presents unique methodological challenges. scATAC-seq experiments sample DNA, which, due to low copy numbers (diploid in humans), lead to inherent data sparsity (1–10% of peaks detected per cell) compared to transcriptomic (scRNA-seq) data (10–45% of expressed genes detected per cell). Such challenges in data generation emphasize the need for informative features to assess cell heterogeneity at the chromatin level. Results We present a benchmarking framework that …

Epigenomicslcsh:QH426-470Test data generationComputer scienceCellATAC-seqComputational biologyBiologyClusteringTranscriptomeMice03 medical and health scienceschemistry.chemical_compound0302 clinical medicinemedicineAnimalsHumansProfiling (information science)scATAC-seqnatural sciencesEpigeneticsFeature matrixCluster analysislcsh:QH301-705.5GeneTransposaseVisualization030304 developmental biologySparse matrix0303 health sciencesFeaturizationDimensionality reductionResearchComputational BiologySequence Analysis DNADimensionality reductionChromatinBenchmarkinglcsh:Geneticsmedicine.anatomical_structurelcsh:Biology (General)chemistryRegulatory genomicsSingle-Cell AnalysisPeak calling030217 neurology & neurosurgeryDNA
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Common genes associated with antidepressant response in mouse and man identify key role of glucocorticoid receptor sensitivity.

2017

Response to antidepressant treatment in major depressive disorder (MDD) cannot be predicted currently, leading to uncertainty in medication selection, increasing costs, and prolonged suffering for many patients. Despite tremendous efforts in identifying response-associated genes in large genome-wide association studies, the results have been fairly modest, underlining the need to establish conceptually novel strategies. For the identification of transcriptome signatures that can distinguish between treatment responders and nonresponders, we herein submit a novel animal experimental approach focusing on extreme phenotypes. We utilized the large variance in response to antidepressant treatmen…

0301 basic medicineMicroarraysPhysiologyGene ExpressionBioinformaticsBiochemistryBiomarkers PharmacologicalTranscriptomeMice0302 clinical medicineGlucocorticoid receptorMedicine and Health SciencesBiology (General)DepressionGeneral NeuroscienceBrainDrugsAntidepressantsPhenotypeAntidepressive Agents3. Good healthBody FluidsParoxetineBioassays and Physiological AnalysisBloodMice Inbred DBAMultigene FamilyMajor depressive disorderAntidepressantDNA microarrayAnatomyGeneral Agricultural and Biological SciencesResearch ArticleQH301-705.5Antidepressant drug therapy ; Blood ; Gene regulation ; Biomarkers ; Depression ; Gene expression ; Microarrays ; AntidepressantsBiologyResearch and Analysis MethodsGeneral Biochemistry Genetics and Molecular BiologyBlood Plasma03 medical and health sciencesReceptors GlucocorticoidMental Health and PsychiatrymedicineGeneticsAnimalsHumansGene RegulationPharmacologyDepressive Disorder MajorGeneral Immunology and MicrobiologyMechanism (biology)Mood DisordersGene Expression ProfilingBiology and Life Sciencesmedicine.diseaseGene expression profiling030104 developmental biologyGene Expression RegulationCorticosterone030217 neurology & neurosurgeryBiomarkersPLoS biology
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