KODAMA (version 1.6)

multi_continuous_table: Continuous Information

Description

Summarization of the continuous information.

Usage

multi_continuous_table (data, 
                        label, 
                        digits = 0, 
                        scientific = FALSE,
                        range=c("IQR","95%CI"),
                        logchange=FALSE)

Arguments

data

the matrix containing the continuous values. Each row corresponds to a different sample. Each column corresponds to a different variable.

label

the classification of the cohort.

digits

how many significant digits are to be used.

scientific

either a logical specifying whether result should be encoded in scientific format.

range

the range to be visualized.

logchange

either a logical specifying whether log2 of fold change should be visualized.

Value

The function returns a table with the summarized information. If the number of group is equal to two, the p-value is computed using the Wilcoxon rank-sum test, Kruskal-Wallis test otherwise.

References

Cacciatore S, Luchinat C, Tenori L Knowledge discovery by accuracy maximization. Proc Natl Acad Sci U S A 2014;111(14):5117-22. doi: 10.1073/pnas.1220873111. Link

Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA KODAMA: an updated R package for knowledge discovery and data mining. Bioinformatics 2017;33(4):621-623. doi: 10.1093/bioinformatics/btw705. Link

See Also

continuous_table, categorical_table, txtsummary

Examples

# NOT RUN {
data(clinical)


multi_continuous_table(data=clinical[,c("BMI","Age")],digits = 1,label=clinical[,"Hospital"])

# }