Description Usage Arguments Details Value Author(s) Examples
This function summarize the dataframe (based on a column). It has additional controls to group samples and to omit variables not needed.
1 |
dataframe |
data in dataframe format |
y |
column name whose values has to be summarized (column elements need to be numeric |
grp_vector |
a character vector of column names whose order indicate the order of grouping. |
rm_vector |
a character vector of items that need to be omitted before summarizing. |
nickname |
label name for the entries in output dataframe. |
rm |
rm = "FALSE" if outliers not to be removed, rm = "TRUE" If outliers to be removed. |
param |
a vector of parameters for more stringent outlier removal. param has to be entered in the format c(strict, cutoff, n). For details please refer |
This function first remove 'rm_vector' elements from the 'dataframe'. Samples are grouped (each level of a 'grp_vector' element as separate group) and sorted (based on 'grp_vector' elements order). column 'y' is then summarized for each group (please refer rmodd_summary
: for details.
A dataframe. First columns are named as grp_vector elements. Followed by a 'label' column (element is 'nickname').This 'label' column will be useful when analyzing multiple plates. Summary statistics of 'y' appear as columns: N (number of samples/group), Mean (average/group), SD (standard deviation/group) and CV (percentage cv/group)
A.A Palakkan
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## loading data
data(metafile384, rawdata384)
rawdata<-plate2df(data2plateformat(rawdata384,platetype = 384))
data_DF2<- dplyr::inner_join(rawdata,metafile384,by=c("row","col","position"))
## eg:1 summarising the 'value' after grouping samples and omitting blanks.
# grouping order cell, compound, concentration and type.
result2 <- dfsummary(data_DF2,y = "value",
grp_vector = c("cell","compound","concentration","type"),
rm_vector = c("blank1","blank2","blank3","blank4"),
nickname = "384well",
rm = "FALSE",param = c(strict="FALSE",cutoff=40,n=12))
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