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.
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.