bioassays (version 1.0.1)

pvalue: t-Test on Summary Dataframe

Description

This function calculate the significance (t-test) within groups of 'dataframe'

Usage

pvalue (dataframe, control, sigval)

Arguments

dataframe

a summary dataframe of dfsummary output

control

control group name

sigval

pvalue cutoff for significance

Value

A dataframe. New columns named 'pvalue' (p values of t-test.If the value is less than 0.001, then appear as "< 0.001") and 'significance' (yes if pvalue less than 'sigval') are attached to the left.

Details

The 'dataframe' should be having similar format of dfsummary output. 'control' should be an element from the column just before 'label'. 'N', 'Mean', 'SD' and 'CV' columns in the 'dataframe' are used for calculating p value by t-test (one to one t-test with 'control' in that group). significant if pvalue is < 'sigval'. Different groups in 'dataframe' are evaluated separately (columns before label is used for grouping).

Examples

# NOT RUN {
## loading data
data(metafile384, rawdata384)
rawdata<-plate2df(data2plateformat(rawdata384,platetype = 384))
data_DF2<- dplyr::inner_join(rawdata,metafile384,by=c("row","col","position"))
result3 <- dfsummary(data_DF2,y = "value",
                    grp_vector = c("cell","compound","concentration"),
                    rm_vector = c("B", "drug2", "huh7"),
                    nickname = "",
                    rm = "FALSE", param = c(strict = "FALSE", cutoff = 40,n = 12))

## eg:1 t-test on result3.
pvalue(result3,"C3",sigval=0.05)

# }