Featured Publications
High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin
Achim K, Pettit J, Saraiva L, Gavriouchkina D, Larsson T, Arendt D, Marioni J. High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. Nature Biotechnology 2015, 33: 503-509. PMID: 25867922, DOI: 10.1038/nbt.3209.Peer-Reviewed Original Research
2015
Computational assignment of cell-cycle stage from single-cell transcriptome data
Scialdone A, Natarajan K, Saraiva L, Proserpio V, Teichmann S, Stegle O, Marioni J, Buettner F. Computational assignment of cell-cycle stage from single-cell transcriptome data. Methods 2015, 85: 54-61. PMID: 26142758, DOI: 10.1016/j.ymeth.2015.06.021.Peer-Reviewed Original ResearchConceptsCell cycle stageTranscriptomes of single cellsPopulation of cellsSingle-cell transcriptomic dataSingle cellsCell cycle signatureTranscriptome dataCellular statesRNA sequencingCell cycleExpression profilesCell typesTranscriptomePublished datasetsCaptured cellsCustomized predictorCellsComputational approachSupervised machine learning methodsMachine learning methodsNormalisation strategyComputational assignmentLearning methodsPCA-based approach