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James B. Brown

  1. Measuring reproducibility of high-throughput experiments.

    Mon, 10/24/2011 - 15:01 — SomNambul
    Authors: Peter J. Bickel, James B. Brown, Haiyan Huang, Qunhua Li
    Subjects: Applications
    Abstract

    Reproducibility is essential to reliable scientific discovery in
    high-throughput experiments. In this work we propose a unified approach to
    measure the reproducibility of findings identified from replicate experiments
    and identify putative discoveries using reproducibility. Unlike the usual
    scalar measures of reproducibility, our approach creates a curve, which
    quantitatively assesses when the findings are no longer consistent across
    replicates.

  2. Subsampling Methods for genomic inference.

    Thu, 01/06/2011 - 16:01 — SomNambul
    Authors: Peter J. Bickel, Nathan Boley, James B. Brown, Haiyan Huang, Nancy R. Zhang
    Subjects: Applications
    Abstract

    Large-scale statistical analysis of data sets associated with genome
    sequences plays an important role in modern biology. A key component of such
    statistical analyses is the computation of $p$-values and confidence bounds for
    statistics defined on the genome. Currently such computation is commonly
    achieved through ad hoc simulation measures. The method of randomization, which
    is at the heart of these simulation procedures, can significantly affect the
    resulting statistical conclusions.

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