Description Usage Arguments Details Value Author(s) Examples
The method normalizes count data by the trimmed mean of m values in each sample
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e_data |
a p \times n data.frame of count data, where p is the number of features and n is the number of samples. Each row corresponds to data for a feature, with the first column giving the feature name. |
edata_id |
character string indicating the name of the feature identifier. Usually obtained by calling |
reference |
which column in e_data should be used as the reference, default is to use the sample with the least amount of missing data. |
qm |
percentage by which to trim M values (gene-wise log-fold-changes), default is 0.30 (30%) |
qa |
percentage by which to trim A values (absolute expression levels), default is 0.05 (5%) |
Count data is normalized by the trimmed mean of m values.
List containing 3 elements: norm_data is a data.frame with same structure as e_data that contains the TMM-normalized data, location_param is a numeric vector of the TMM values for each sample, and scale_param is NULL.
Allison Thompson, Lisa Bramer
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