pvalue: t-Test on Summary Dataframe

In bioassays: Summarising Multi Well Plate Cellular Assay

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

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).

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.

Author(s)

A.A Palakkan

Examples

## 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)

bioassays documentation built on Oct. 23, 2020, 6:48 p.m.