View source: R/outlierDetect.R
outlierDetect | R Documentation |
This function allows users to perform outlier analysis on bulk data by calculating z-score. Outlier genes defined as mean/SD = |Z| > z_cutoff.
outlierDetect( data_object, z_cutoff = NULL, plotWidth = 10, plotHeight = 5, group_column = NULL, cl = 2, fileName = NULL, filePATH = NULL )
data_object |
Input PALMO S4 object. It contains annotation information and expression data from Bulk or single cell data. |
z_cutoff |
|Z| cutoff threshold to find potential outliers (Eg.
z_cutoff=2, equals to |
plotWidth |
User-defined plot width, Default 10 in |
plotHeight |
User-defined plot height, Default 5 in |
group_column |
Include group by outlier analysis (celltype, cluster) |
cl |
Number of clusters. Use nCores-1 to run parallel. Default 2 |
fileName |
User-defined file name, Default outputFile |
filePATH |
User-defined output directory PATH Default, current directory |
PALMO object with outlier_res dataframe
## Not run: palmo_obj <- outlierDetect(data_object=palmo_obj, z_cutoff=2) ## End(Not run)
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