dp.ht {divo} | R Documentation |
dp.ht Diversity Profile with the Horvitz-Thompson Adjustment
Description
Calculates diversity profile with the Horvitz-Thompson adjustment (DP-HT), as defined in Rempala and Seweryn (2013) using the Renyi entropy (Renyi 1961) as a diversity measure. The function calculates the Renyi entropy values for a given range of the Renyi index (the index should be greater than 0). When the index is less then one, the rare counts are up-weighted and when it is greater than one, the rare counts are down-weighted. Since the Renyi entropy is a non-increasing function of the index, the profile plot should be always non-increasing. For more information, see Rempala and Seweryn (2013).
Usage
dp.ht(x, alpha = seq(0.1, 2, 0.1), CI = 0.95, resample = 100,
single_graph = FALSE, pooled_graph = FALSE, csv_output = FALSE,
PlugIn = FALSE, size = 1, CVG = FALSE, saveBootstrap = FALSE)
Arguments
x |
a matrix containing input populations |
alpha |
a vector containing alpha values, default = seq(0.1, 2, 0.1) |
CVG |
a vector containing alpha values multiplied by coverage; default = FALSE |
CI |
Confidence Interval default = 0.95, range (0, 1) |
resample |
set number of repetitions, default = 100 |
single_graph |
default = FALSE, plot of the Diversity Profile for each population; |
pooled_graph |
default = FALSE, plot of the Diversity Profile for all populations; |
csv_output |
save the result of the analysis as .CSV file, default = FALSE; |
PlugIn |
standard plug-in estimator, default = FALSE |
size |
resampled fraction of the population, default = 1 (actual size of populations). The value should not be smaller than 10% of population (size = 0.1) |
saveBootstrap |
Saves bootstrap result to a file. Use saveBootstrap = TRUE to save bootstrap results to a Bootstrap folder in current directory; saveBootstrap = 'FolderName' - saves bootstrap results to user-named folder |
Author(s)
Christoph Sadee, Maciej Pietrzak, Michal Seweryn, Cankun Wang, Grzegorz Rempala
Maintainer: Maciej Pietrzak pietrzak.20@osu.edu
References
Rempala G.A., Seweryn M. (2013) Methods for diversity and overlap analysis in T-cell receptor populations. J Math Biol 67:1339-68
Renyi P. (1961) On measures of information and entropy. In: Proceedings of the 4th Berkeley symposium on mathematics, statistics and probability, pp 547-61
Tothmeresz B. (1995) Comparison of different methods for diversity ordering. J Veget Sci 6:283-90
Examples
data(TCR.Data)
result <- dp.ht(x, PlugIn = TRUE)