Hakutulokset - Mark D. Robinson

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  1. 1
    A scaling normalization method for differential expression analysis of RNA-seq data

    A scaling normalization method for differential expression analysis of RNA-seq data Tekijä Mark D. Robinson, Alicia Oshlack

    Julkaistu 2010
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  2. 2
    iCOBRA: open, reproducible, standardized and live method benchmarking

    iCOBRA: open, reproducible, standardized and live method benchmarking Tekijä Charlotte Soneson, Mark D. Robinson

    Julkaistu 2016
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  3. 3
    DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics

    DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics Tekijä Małgorzata Nowicka, Mark D. Robinson

    Julkaistu 2016
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  4. 4
    Towards unified quality verification of synthetic count data with <i>countsimQC</i>

    Towards unified quality verification of synthetic count data with <i>countsimQC</i> Tekijä Charlotte Soneson, Mark D. Robinson

    Julkaistu 2017
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  5. 5
    Bias, robustness and scalability in single-cell differential expression analysis

    Bias, robustness and scalability in single-cell differential expression analysis Tekijä Charlotte Soneson, Mark D. Robinson

    Julkaistu 2018
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  6. 6
    DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics

    DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics Tekijä Małgorzata Nowicka, Mark D. Robinson

    Julkaistu 2016
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  7. 7
    A comparison of Affymetrix gene expression arrays

    A comparison of Affymetrix gene expression arrays Tekijä Mark D. Robinson, Terence P. Speed

    Julkaistu 2007
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  8. 8
    Moderated statistical tests for assessing differences in tag abundance

    Moderated statistical tests for assessing differences in tag abundance Tekijä Mark D. Robinson, Gordon K. Smyth

    Julkaistu 2007
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  9. 9
    Comparison of clustering methods for high‐dimensional single‐cell flow and mass cytometry data

    Comparison of clustering methods for high‐dimensional single‐cell flow and mass cytometry data Tekijä Lukas M. Weber, Mark D. Robinson

    Julkaistu 2016
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  10. 10
    Robustly detecting differential expression in RNA sequencing data using observation weights

    Robustly detecting differential expression in RNA sequencing data using observation weights Tekijä Xiaobei Zhou, Helen Lindsay, Mark D. Robinson

    Julkaistu 2014
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  11. 11
    Electronic Health Record Effects on Work-Life Balance and Burnout Within the I3 Population Collaborative

    Electronic Health Record Effects on Work-Life Balance and Burnout Within the I3 Population Collaborative Tekijä Sandy Robertson, Mark D. Robinson, Alfred Reid

    Julkaistu 2017
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  12. 12
    A systematic performance evaluation of clustering methods for single-cell RNA-seq data

    A systematic performance evaluation of clustering methods for single-cell RNA-seq data Tekijä Angelo Duò, Mark D. Robinson, Charlotte Soneson

    Julkaistu 2018
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  13. 13
    A systematic performance evaluation of clustering methods for single-cell RNA-seq data

    A systematic performance evaluation of clustering methods for single-cell RNA-seq data Tekijä Angelo Duò, Mark D. Robinson, Charlotte Soneson

    Julkaistu 2020
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  14. 14
    A systematic performance evaluation of clustering methods for single-cell RNA-seq data

    A systematic performance evaluation of clustering methods for single-cell RNA-seq data Tekijä Angelo Duò, Mark D. Robinson, Charlotte Soneson

    Julkaistu 2018
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  15. 15
    From RNA-seq reads to differential expression results

    From RNA-seq reads to differential expression results Tekijä Alicia Oshlack, Mark D. Robinson, Matthew D. Young

    Julkaistu 2010
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  16. 16
    Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

    Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences Tekijä Charlotte Soneson, Michael I. Love, Mark D. Robinson

    Julkaistu 2015
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  17. 17
    pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single cell RNA-seq preprocessing tools

    pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single cell RNA-seq preprocessing tools Tekijä Pierre‐Luc Germain, Anthony Sonrel, Mark D. Robinson

    Julkaistu 2020
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  18. 18
    Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences

    Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences Tekijä Charlotte Soneson, Michael I. Love, Mark D. Robinson

    Julkaistu 2016
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  19. 19
    stageR: a general stage-wise method for controlling the gene-level false discovery rate in differential expression and differential transcript usage

    stageR: a general stage-wise method for controlling the gene-level false discovery rate in differential expression and differential transcript usage Tekijä Koen Van den Berge, Charlotte Soneson, Mark D. Robinson

    Julkaistu 2017
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  20. 20
    FunSpec: a web-based cluster interpreter for yeast

    FunSpec: a web-based cluster interpreter for yeast Tekijä Mark D. Robinson, Jörg Grigull, Naveed Mohammad, Timothy R. Hughes

    Julkaistu 2002
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