fluidigmSC_identifyExpOutliers: An outlier detection function
In uSORT: uSORT: A self-refining ordering pipeline for gene selection

An outlier detection function identifies cells with median expression below that of the bulk, reproduced from FluidigmSC package.

fluidigmSC_identifyExpOutliers(log2ex_data, expression_data_raw, threshold,
  step, fine_step, num_fine_test, pct_goodsample_threshold = 0.5,
  quantile_threshold = 0.95, low_quantile_threshold = 0.25,
  min_gene_number = 25, lod)

`log2ex_data`	A data frame containing log2 tranformed expression values, with rownames of genes and colnames of cells.
`expression_data_raw`	A data frame containing raw expression values, with rownames of genes and colnames of cells.
`threshold`	A value in raw expression used as the starting threshold value.
`step`	An integer number indicating the increment of threshold value at each iteration.
`fine_step`	An integer number indicating the increment of threshold value at each iteration, at the refining stage.
`num_fine_test`	An integer number indicating the number of iteration of the refining stage.
`pct_goodsample_threshold`	A fraction value indicating the minimum percentage of samples on which the representative genes are detectable.
`quantile_threshold`	A probability of gene detection rate above which a sample is considered as good sample.
`low_quantile_threshold`	A probability of average gene expression value below which a sample is taken as an outlier.
`min_gene_number`	An integer indicating the minimum size of representative genes.
`lod`	A value of limit of detection in the unit of TPM/CPM/RPKM.