runKappa: Run consistency evaluation using Kappa statistic

In xlucpu/MOVICS: Multi-Omics integration and VIsualization in Cancer Subtyping

Description

Calculate Kappa statistic to measure the consistency between two appraisements

Usage

runKappa(
  subt1 = NULL,
  subt2 = NULL,
  subt1.lab = NULL,
  subt2.lab = NULL,
  fig.path = getwd(),
  fig.name = "constheatmap",
  width = 5,
  height = 5
)

Arguments

subt1	A numeric vector to indicate the first appraisement. Order should be exactly the same with subt2 for each sample.
subt2	A numeric vector to indicate the second appraisement. Order should be exactly the same with subt1 for each sample.
subt1.lab	A string value to indicate the label of the first subtype.
subt2.lab	A string value to indicate the label of the second subtype.
fig.path	A string value to indicate the output path for storing the consistency heatmap.
fig.name	A string value to indicate the name of the consistency heatmap.
width	A numeric value to indicate the width of output figure.
height	A numeric value to indicate the height of output figure.

Details

This function evaluates the consistency between two appraisements that targets to the same cohort. For example, the NTP-predicted subtype amd PAM-predicted subtype of external cohort, or the current subtype and predicted subtype of discovery cohort. Therefore, the arguments 'subt1' and 'subt2' can be the 'clust' column of 'clust.res' derived from 'getMOIC()' with one specified algorithm or 'get%algorithm_name%' or 'getConsensusMOIC()' with a list of multiple algorithms or 'runNTP()' or 'runPAM()'. However, subtypes identified from different algorithm (i.e., 'get%algorithm_name1%' and 'get%algorithm_name2%') can not be evaluated because the subtype 1 identified from the first algorithm may not be the same subtype 1 from the second algorithm.

Value

A figure of consistency heatmap (.pdf).

Examples

# There is no example and please refer to vignette.

xlucpu/MOVICS documentation built on July 24, 2021, 9:23 p.m.