View source: R/data_filtering.R
keep_non_zero_percentage | R Documentation |
Given a value matrix (features are rows, samples are columns), and sample classes, find those things that are not zero in at least a certain number of samples in one of the classes, and keep those features for further processing.
keep_non_zero_percentage(
data_matrix,
sample_classes = NULL,
keep_num = 0.75,
zero_value = 0,
all = FALSE
)
data_matrix |
the matrix of values to work with |
sample_classes |
the classes of each sample |
keep_num |
what number of samples in each class need a non-zero value (see Details) |
zero_value |
what number represents zero values |
all |
is this an either / or OR does it need to be present in all? |
The number of samples that must be non-zero can be expressed either as a whole number (that is greater than one), or as a fraction that will be be multiplied by the number of samples in each class to get the lower limits for each of the classes.
logical
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