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# ==================================================================== #
# TITLE #
# Antimicrobial Resistance (AMR) Data Analysis for R #
# #
# SOURCE #
# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2021 Berends MS, Luz CF et al. #
# Developed at the University of Groningen, the Netherlands, in #
# collaboration with non-profit organisations Certe Medical #
# Diagnostics & Advice, and University Medical Center Groningen. #
# #
# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
resistance_data <- structure(list(order = c("Bacillales", "Enterobacterales", "Enterobacterales"),
genus = c("Staphylococcus", "Escherichia", "Klebsiella"),
AMC = c(0.00425, 0.13062, 0.10344),
CXM = c(0.00425, 0.05376, 0.10344),
CTX = c(0.00000, 0.02396, 0.05172),
TOB = c(0.02325, 0.02597, 0.10344),
TMP = c(0.08387, 0.39141, 0.18367)),
class = c("grouped_df", "tbl_df", "tbl", "data.frame"),
row.names = c(NA, -3L),
groups = structure(list(order = c("Bacillales", "Enterobacterales"),
.rows = list(1L, 2:3)),
row.names = c(NA, -2L),
class = c("tbl_df", "tbl", "data.frame"),
.drop = TRUE))
pca_model <- pca(resistance_data)
expect_inherits(pca_model, "pca")
pdf(NULL) # prevent Rplots.pdf being created
if (AMR:::pkg_is_available("ggplot2")) {
ggplot_pca(pca_model, ellipse = TRUE)
ggplot_pca(pca_model, arrows_textangled = FALSE)
}
if (AMR:::pkg_is_available("dplyr", min_version = "1.0.0")) {
resistance_data <- example_isolates %>%
group_by(order = mo_order(mo),
genus = mo_genus(mo)) %>%
summarise_if(is.rsi, resistance, minimum = 0)
pca_result <- resistance_data %>%
pca(AMC, CXM, CTX, CAZ, GEN, TOB, TMP, "SXT")
expect_inherits(pca_result, "prcomp")
if (AMR:::pkg_is_available("ggplot2")) {
ggplot_pca(pca_result, ellipse = TRUE)
ggplot_pca(pca_result, ellipse = FALSE, arrows_textangled = FALSE, scale = FALSE)
}
}