Description Usage Arguments Value
Identify outliers across samples and across features and set identified values to NA. Features and samples that contain a threshold ratio of NA values are removed.
1 | clean_bmdk(dat, naThreshold = 0.05, sdMultiplier = 4)
|
dat |
a list containing 3 elements: case, a list of case/control statuses; feat, a matrix of normalized feature data; maxfeat, a list of max features from each column in feat |
naThreshold |
Proportion of NAs to allow before dropping a sample or feature due to missingness. |
sdMultiplier |
Number of standard deviations defining the threshold for outlier detection. Any values above sdMultiplier standard deviations away from the mean will be removed as an outlier. |
List containing 3 elements (case, feat, maxfeat) with relevant NA values and necessary features/samples removed
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