Description Usage Arguments Details Value
This function applies the centered logratio transformation on a matrix of expression values.
1 2 3 | clr_transformation(mat, base = "e", remove_zeros = FALSE,
denom_method = "geomean", impute_method = "multiplicative",
delta = NULL, impute_proportion = 0.65)
|
mat |
N x M matrix of estimated abundances |
base |
what should the base of the logarithm be? currently only supports base "e" and base 2. |
remove_zeros |
boolean to see if this function
should remove essential zeros (features with zeros in
all samples). The default is |
denom_method |
either 'geomean' or 'DESeq2' to use either the geometric mean of all features as the denominator, or the DESeq2-style size factors as the denominator (equivalent to using standard DESeq2-style normalization, which is used in standard sleuth) |
impute_method |
which method to use for imputing zeros. 'multiplicative' (default) sets all values smaller than a imputation value 'delta' (determined by delta or impute_proportion) to that imputation value, and reduces all other values by the amount X * (1 - delta*num_zero_values / sum_constraint). 'additive' is similar to most other tools, and just adds the imputation value to all entries ('delta' must be specified) |
delta |
a number that is the imputed value. If |
impute_proportion |
percentage of minimum value that
becomes the imputed value. Only used if delta is |
this converts an N x M matrix of N target IDs and M samples (N >> M). If M > N, then the matrix is flipped to do the calculations, but returned with the same as the input. The calculation is as follows: x_1, x_2, ..., x_D => log(x_1 / g(X)), ..., log(x_D / g(X))
N x M matrix of CLR-transformed values with essential zero rows removed.
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