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evaluate_flowClust.R
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#########################################################################################
# R script to load and evaluate results for flowClust
#
# Lukas Weber, August 2016
#########################################################################################
library(flowCore)
library(clue)
# helper functions to match clusters and evaluate
source("../helpers/helper_match_evaluate_multiple.R")
source("../helpers/helper_match_evaluate_single.R")
source("../helpers/helper_match_evaluate_FlowCAP.R")
source("../helpers/helper_match_evaluate_FlowCAP_alternate.R")
# which set of results to use: automatic or manual number of clusters (see parameters spreadsheet)
RES_DIR_FLOWCLUST <- "../../results/manual/flowClust"
DATA_DIR <- "../../../benchmark_data_sets"
# which data sets required subsampling for this method (see parameters spreadsheet)
is_subsampled <- c(TRUE, TRUE, TRUE, TRUE, FALSE, TRUE, FALSE, FALSE)
# alternate FlowCAP results at the end
is_rare <- c(FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE)
is_FlowCAP <- c(FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE)
n_FlowCAP <- 2
####################################################
### load truth (manual gating population labels) ###
####################################################
# files with true population labels (subsampled labels if subsampling was required for
# this method; see parameters spreadsheet)
files_truth <- list(
Levine_32dim = file.path(RES_DIR_FLOWCLUST, "true_labels_flowClust_Levine_32dim.txt"),
Levine_13dim = file.path(RES_DIR_FLOWCLUST, "true_labels_flowClust_Levine_13dim.txt"),
Samusik_01 = file.path(RES_DIR_FLOWCLUST, "true_labels_flowClust_Samusik_01.txt"),
Samusik_all = file.path(RES_DIR_FLOWCLUST, "true_labels_flowClust_Samusik_all.txt"),
Nilsson_rare = file.path(DATA_DIR, "Nilsson_rare/data/Nilsson_rare.fcs"),
Mosmann_rare = file.path(RES_DIR_FLOWCLUST, "true_labels_flowClust_Mosmann_rare.txt"),
FlowCAP_ND = file.path(DATA_DIR, "FlowCAP_ND/data/FlowCAP_ND.fcs"),
FlowCAP_WNV = file.path(DATA_DIR, "FlowCAP_WNV/data/FlowCAP_WNV.fcs")
)
# extract true population labels
clus_truth <- vector("list", length(files_truth))
names(clus_truth) <- names(files_truth)
for (i in 1:length(clus_truth)) {
if (!is_subsampled[i]) {
data_truth_i <- flowCore::exprs(flowCore::read.FCS(files_truth[[i]], transformation = FALSE, truncate_max_range = FALSE))
} else {
data_truth_i <- read.table(files_truth[[i]], header = TRUE, stringsAsFactors = FALSE)
}
clus_truth[[i]] <- data_truth_i[, "label"]
}
sapply(clus_truth, length)
# cluster sizes and number of clusters
# (for data sets with single rare population: 1 = rare population of interest, 0 = all others)
tbl_truth <- lapply(clus_truth, table)
tbl_truth
sapply(tbl_truth, length)
# store named objects (for other scripts)
files_truth_flowClust <- files_truth
clus_truth_flowClust <- clus_truth
##############################
### load flowClust results ###
##############################
# load cluster labels
files_out <- list(
Levine_32dim = file.path(RES_DIR_FLOWCLUST, "flowClust_labels_Levine_32dim.txt"),
Levine_13dim = file.path(RES_DIR_FLOWCLUST, "flowClust_labels_Levine_13dim.txt"),
Samusik_01 = file.path(RES_DIR_FLOWCLUST, "flowClust_labels_Samusik_01.txt"),
Samusik_all = file.path(RES_DIR_FLOWCLUST, "flowClust_labels_Samusik_all.txt"),
Nilsson_rare = file.path(RES_DIR_FLOWCLUST, "flowClust_labels_Nilsson_rare.txt"),
Mosmann_rare = file.path(RES_DIR_FLOWCLUST, "flowClust_labels_Mosmann_rare.txt"),
FlowCAP_ND = file.path(RES_DIR_FLOWCLUST, "flowClust_labels_FlowCAP_ND.txt"),
FlowCAP_WNV = file.path(RES_DIR_FLOWCLUST, "flowClust_labels_FlowCAP_WNV.txt")
)
clus <- vector("list", length(files_out))
names(clus) <- names(files_out)
# skip data set Levine_32dim
for (i in 2:length(clus)) {
clus[[i]] <- read.table(files_out[[i]], header = TRUE, stringsAsFactors = FALSE)[, "label"]
}
sapply(clus, length)
# cluster sizes and number of clusters
# (for data sets with single rare population: 1 = rare population of interest, 0 = all others)
tbl <- lapply(clus, table)
tbl
sapply(tbl, length)
# contingency tables
# (excluding FlowCAP data sets since population IDs are not consistent across samples)
# skip data set Levine_32dim
for (i in 2:length(clus)) {
if (!is_FlowCAP[i]) {
print(table(clus[[i]], clus_truth[[i]]))
}
}
# store named objects (for other scripts)
files_flowClust <- files_out
clus_flowClust <- clus
###################################
### match clusters and evaluate ###
###################################
# see helper function scripts for details on matching strategy and evaluation
res <- vector("list", length(clus) + n_FlowCAP)
names(res)[1:length(clus)] <- names(clus)
names(res)[-(1:length(clus))] <- paste0(names(clus)[is_FlowCAP], "_alternate")
# skip data set Levine_32dim
for (i in 2:length(clus)) {
if (!is_rare[i] & !is_FlowCAP[i]) {
res[[i]] <- helper_match_evaluate_multiple(clus[[i]], clus_truth[[i]])
} else if (is_rare[i]) {
res[[i]] <- helper_match_evaluate_single(clus[[i]], clus_truth[[i]])
} else if (is_FlowCAP[i]) {
res[[i]] <- helper_match_evaluate_FlowCAP(clus[[i]], clus_truth[[i]])
res[[i + n_FlowCAP]] <- helper_match_evaluate_FlowCAP_alternate(clus[[i]], clus_truth[[i]])
}
}
# store named object (for plotting scripts)
res_flowClust <- res