Generate a Table with Fold Change
gentab_FC.RdGiven a dataframe and a set of numerical variables of that dataframe, it performs fold changes analysis to each desired variable and creates a new table.
Usage
gentab_FC(
df,
v,
f,
second_to_first_ratio = TRUE,
paired = FALSE,
are_log_transf = FALSE,
log_base = 2,
filter_sign = FALSE,
FCcutoff = 2
)Arguments
- df
a dataframe.
- v
a character vector. Each element must correspond to a column name of the df, each of which must contain numeric values.
- f
character vector of length 1. Name of the column of df containing the factor variable (that must have exactly 2 levels) considered for performing the Fold Change analysis.
- second_to_first_ratio
logical. If TRUE the second group/first group ratio will be computed, if FALSE the first group/second group ratio will be computed.
- paired
logical. If FALSE it performs FC on mean of the two groups. If TRUE it performs FC for each pair and then compute the mean.
- are_log_transf
logical. If you really need to perform this FC analysis on already log-transformed data, specify here as TRUE, and the subtraction will be performed instead of the ration.
- log_base
numeric of length 1. Specify here the base of the logarithm to calculate the logFC or, if are_log_transf is TRUE; the base of the logarithm the that were used to transform the data.
- filter_sign
logical. If TRUE, the table will be filtered and only those that passed the FCcutoff will be retained.
- FCcutoff
numeric of length 1. If filter_sign is TRUE, the value of the FCcutoff to consider a feature difference as significant.