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  • how to remove the outlier samples in gene microarray analysis

    We used principal component (PC) analysis to identify and remove outlier
    samples. We converted each sample into a z score statistic, based on the
    squared distance of its 1st PC from the population mean. The z statistic
    was converted to a false-discovery rate with the Gaussian cumulative
    distribution and the Benjamini-Hochberg procedure (Benjamini and Hochberg,
    1995). Samples falling below an FDR of 0.2 were designated at outliers and
    removed. This filtering procedure was performed iteratively until no samples
    were determined to be an outlier. A total of 24 samples were removed in this
    manner.


    this is a method discribed in a paper, however, i cann't fully understand. what the z statistic which converted to a fdr and used as a cutoff to remove the outlier samples? we should i do step by step? z score transformation, and then ...? hope your help, thank you very much.

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