Analyses/consensus_sequences/create_tables_paper.R
In thednainus/HIVepisimAnalysis: Functions to analyse results from network analysis
#generate tables for paper
library(xtable)
source("Analyses/consensus_sequences/TP_TN_FP_FN_estimation.R")
source("Analyses/consensus_sequences/TP_TN_FP_FN_estimation_threshold90.R")
#Table for total pairs for consensus sequences
#for main text
#merge data for threshold of 80% and 90% for migration probability of 1/500
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_500mig_s1_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_500mig_s1_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s1_500mig_80_90 <- cbind(all_500mig_s1_80_data2[,c(2:4,8:13)],
all_500mig_s1_90_data2[,c(2:4,8:13)])
s1_500mig_80_90["TP"] <- paste(s1_500mig_80_90$total_TP80, s1_500mig_80_90$total_TP90, sep = "/")
s1_500mig_80_90["FP"] <- paste(s1_500mig_80_90$total_FP80, s1_500mig_80_90$total_FP90, sep = "/")
s1_500mig_80_90["TN"] <- paste(s1_500mig_80_90$total_TN80, s1_500mig_80_90$total_TN90, sep = "/")
s1_500mig_80_90["FN"] <- paste(s1_500mig_80_90$total_FN80, s1_500mig_80_90$total_FN90, sep = "/")
s1_500mig_80_90["Total"] <- paste(s1_500mig_80_90$total80, s1_500mig_80_90$total90, sep = "/")
s1_500mig_80_90["TP wiw"] <- paste(s1_500mig_80_90$total_wiw_within_TP80, s1_500mig_80_90$total_wiw_within_TP90, sep = "/")
final_table_500mig_s1 <- s1_500mig_80_90[c(1:6,37:42,55:60),c(1:3,19:22,24)]
final_table_500mig_s1 <- final_table_500mig_s1[order(final_table_500mig_s1$param,final_table_500mig_s1$perc),]
final_table_500mig_s1 <- final_table_500mig_s1[order(final_table_500mig_s1$code, decreasing = TRUE),]
final_table_500mig_s1["perc"] <- as.factor(as.numeric(final_table_500mig_s1$perc) * 100)
final_table_500mig_s1["param"] <- ifelse(final_table_500mig_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_500mig_s1["Parameter/Tree/Perc."] <- paste(final_table_500mig_s1$param,
final_table_500mig_s1$code,
final_table_500mig_s1$perc,
sep = "/ ")
print(xtable(final_table_500mig_s1[c(9,4:8)]), include.rownames=FALSE)
# sampler 1: for supplementary material ----
#merge data for threshold of 80% and 90% for migration probability of 1/250
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_250mig_s1_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_250mig_s1_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s1_250mig_80_90 <- cbind(all_250mig_s1_80_data2[,c(2:4,8:13)],
all_250mig_s1_90_data2[,c(2:4,8:13)])
s1_250mig_80_90["TP"] <- paste(s1_250mig_80_90$total_TP80, s1_250mig_80_90$total_TP90, sep = "/")
s1_250mig_80_90["FP"] <- paste(s1_250mig_80_90$total_FP80, s1_250mig_80_90$total_FP90, sep = "/")
s1_250mig_80_90["TN"] <- paste(s1_250mig_80_90$total_TN80, s1_250mig_80_90$total_TN90, sep = "/")
s1_250mig_80_90["FN"] <- paste(s1_250mig_80_90$total_FN80, s1_250mig_80_90$total_FN90, sep = "/")
s1_250mig_80_90["Total"] <- paste(s1_250mig_80_90$total80, s1_250mig_80_90$total90, sep = "/")
s1_250mig_80_90["TP wiw"] <- paste(s1_250mig_80_90$total_wiw_within_TP80, s1_250mig_80_90$total_wiw_within_TP90, sep = "/")
s1_250mig_80_90["perc"] <- as.factor(as.numeric(s1_250mig_80_90$perc) * 100)
s1_250mig_80_90["param"] <- ifelse(s1_250mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s1_250mig_80_90["Parameter/Tree/Perc."] <- paste(s1_250mig_80_90$param,
s1_250mig_80_90$code,
s1_250mig_80_90$perc,
sep = "/ ")
final_table_250mig_s1 <- s1_250mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_250mig_s1), include.rownames=FALSE)
#for supplementary material
#merge data for threshold of 80% and 90% for migration probability of 1/500
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_500mig_s1_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_500mig_s1_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s1_500mig_80_90 <- cbind(all_500mig_s1_80_data2[,c(2:4,8:13)],
all_500mig_s1_90_data2[,c(2:4,8:13)])
s1_500mig_80_90["TP"] <- paste(s1_500mig_80_90$total_TP80, s1_500mig_80_90$total_TP90, sep = "/")
s1_500mig_80_90["FP"] <- paste(s1_500mig_80_90$total_FP80, s1_500mig_80_90$total_FP90, sep = "/")
s1_500mig_80_90["TN"] <- paste(s1_500mig_80_90$total_TN80, s1_500mig_80_90$total_TN90, sep = "/")
s1_500mig_80_90["FN"] <- paste(s1_500mig_80_90$total_FN80, s1_500mig_80_90$total_FN90, sep = "/")
s1_500mig_80_90["Total"] <- paste(s1_500mig_80_90$total80, s1_500mig_80_90$total90, sep = "/")
s1_500mig_80_90["TP wiw"] <- paste(s1_500mig_80_90$total_wiw_within_TP80, s1_500mig_80_90$total_wiw_within_TP90, sep = "/")
s1_500mig_80_90["perc"] <- as.factor(as.numeric(s1_500mig_80_90$perc) * 100)
s1_500mig_80_90["param"] <- ifelse(s1_500mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s1_500mig_80_90["Parameter/Tree/Perc."] <- paste(s1_500mig_80_90$param,
s1_500mig_80_90$code,
s1_500mig_80_90$perc,
sep = "/ ")
final_table_500mig_s1 <- s1_500mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_500mig_s1), include.rownames=FALSE)
#for supplementary material
#merge data for threshold of 80% and 90% for migration probability of 1/750
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_750mig_s1_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_750mig_s1_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s1_750mig_80_90 <- cbind(all_750mig_s1_80_data2[,c(2:4,8:13)],
all_750mig_s1_90_data2[,c(2:4,8:13)])
s1_750mig_80_90["TP"] <- paste(s1_750mig_80_90$total_TP80, s1_750mig_80_90$total_TP90, sep = "/")
s1_750mig_80_90["FP"] <- paste(s1_750mig_80_90$total_FP80, s1_750mig_80_90$total_FP90, sep = "/")
s1_750mig_80_90["TN"] <- paste(s1_750mig_80_90$total_TN80, s1_750mig_80_90$total_TN90, sep = "/")
s1_750mig_80_90["FN"] <- paste(s1_750mig_80_90$total_FN80, s1_750mig_80_90$total_FN90, sep = "/")
s1_750mig_80_90["Total"] <- paste(s1_750mig_80_90$total80, s1_750mig_80_90$total90, sep = "/")
s1_750mig_80_90["TP wiw"] <- paste(s1_750mig_80_90$total_wiw_within_TP80, s1_750mig_80_90$total_wiw_within_TP90, sep = "/")
s1_750mig_80_90["perc"] <- as.factor(as.numeric(s1_750mig_80_90$perc) * 100)
s1_750mig_80_90["param"] <- ifelse(s1_750mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s1_750mig_80_90["Parameter/Tree/Perc."] <- paste(s1_750mig_80_90$param,
s1_750mig_80_90$code,
s1_750mig_80_90$perc,
sep = "/ ")
final_table_750mig_s1 <- s1_750mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_750mig_s1), include.rownames=FALSE)
# sampler 2: for supplementary material ----
#merge data for threshold of 80% and 90% for migration probability of 1/250
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_250mig_s2_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_250mig_s2_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s2_250mig_80_90 <- cbind(all_250mig_s2_80_data2[,c(2:4,8:13)],
all_250mig_s2_90_data2[,c(2:4,8:13)])
s2_250mig_80_90["TP"] <- paste(s2_250mig_80_90$total_TP80, s2_250mig_80_90$total_TP90, sep = "/")
s2_250mig_80_90["FP"] <- paste(s2_250mig_80_90$total_FP80, s2_250mig_80_90$total_FP90, sep = "/")
s2_250mig_80_90["TN"] <- paste(s2_250mig_80_90$total_TN80, s2_250mig_80_90$total_TN90, sep = "/")
s2_250mig_80_90["FN"] <- paste(s2_250mig_80_90$total_FN80, s2_250mig_80_90$total_FN90, sep = "/")
s2_250mig_80_90["Total"] <- paste(s2_250mig_80_90$total80, s2_250mig_80_90$total90, sep = "/")
s2_250mig_80_90["TP wiw"] <- paste(s2_250mig_80_90$total_wiw_within_TP80, s2_250mig_80_90$total_wiw_within_TP90, sep = "/")
s2_250mig_80_90["perc"] <- as.factor(as.numeric(s2_250mig_80_90$perc) * 100)
s2_250mig_80_90["param"] <- ifelse(s2_250mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s2_250mig_80_90["Parameter/Tree/Perc."] <- paste(s2_250mig_80_90$param,
s2_250mig_80_90$code,
s2_250mig_80_90$perc,
sep = "/ ")
final_table_250mig_s2 <- s2_250mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_250mig_s2), include.rownames=FALSE)
#for supplementary material
#merge data for threshold of 80% and 90% for migration probability of 1/500
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_500mig_s2_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_500mig_s2_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s2_500mig_80_90 <- cbind(all_500mig_s2_80_data2[,c(2:4,8:13)],
all_500mig_s2_90_data2[,c(2:4,8:13)])
s2_500mig_80_90["TP"] <- paste(s2_500mig_80_90$total_TP80, s2_500mig_80_90$total_TP90, sep = "/")
s2_500mig_80_90["FP"] <- paste(s2_500mig_80_90$total_FP80, s2_500mig_80_90$total_FP90, sep = "/")
s2_500mig_80_90["TN"] <- paste(s2_500mig_80_90$total_TN80, s2_500mig_80_90$total_TN90, sep = "/")
s2_500mig_80_90["FN"] <- paste(s2_500mig_80_90$total_FN80, s2_500mig_80_90$total_FN90, sep = "/")
s2_500mig_80_90["Total"] <- paste(s2_500mig_80_90$total80, s2_500mig_80_90$total90, sep = "/")
s2_500mig_80_90["TP wiw"] <- paste(s2_500mig_80_90$total_wiw_within_TP80, s2_500mig_80_90$total_wiw_within_TP90, sep = "/")
s2_500mig_80_90["perc"] <- as.factor(as.numeric(s2_500mig_80_90$perc) * 100)
s2_500mig_80_90["param"] <- ifelse(s2_500mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s2_500mig_80_90["Parameter/Tree/Perc."] <- paste(s2_500mig_80_90$param,
s2_500mig_80_90$code,
s2_500mig_80_90$perc,
sep = "/ ")
final_table_500mig_s2 <- s2_500mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_500mig_s2), include.rownames=FALSE)
#for supplementary material
#merge data for threshold of 80% and 90% for migration probability of 1/750
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_750mig_s2_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_750mig_s2_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s2_750mig_80_90 <- cbind(all_750mig_s2_80_data2[,c(2:4,8:13)],
all_750mig_s2_90_data2[,c(2:4,8:13)])
s2_750mig_80_90["TP"] <- paste(s2_750mig_80_90$total_TP80, s2_750mig_80_90$total_TP90, sep = "/")
s2_750mig_80_90["FP"] <- paste(s2_750mig_80_90$total_FP80, s2_750mig_80_90$total_FP90, sep = "/")
s2_750mig_80_90["TN"] <- paste(s2_750mig_80_90$total_TN80, s2_750mig_80_90$total_TN90, sep = "/")
s2_750mig_80_90["FN"] <- paste(s2_750mig_80_90$total_FN80, s2_750mig_80_90$total_FN90, sep = "/")
s2_750mig_80_90["Total"] <- paste(s2_750mig_80_90$total80, s2_750mig_80_90$total90, sep = "/")
s2_750mig_80_90["TP wiw"] <- paste(s2_750mig_80_90$total_wiw_within_TP80, s2_750mig_80_90$total_wiw_within_TP90, sep = "/")
s2_750mig_80_90["perc"] <- as.factor(as.numeric(s2_750mig_80_90$perc) * 100)
s2_750mig_80_90["param"] <- ifelse(s2_750mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s2_750mig_80_90["Parameter/Tree/Perc."] <- paste(s2_750mig_80_90$param,
s2_750mig_80_90$code,
s2_750mig_80_90$perc,
sep = "/ ")
final_table_750mig_s2 <- s2_750mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_750mig_s2), include.rownames=FALSE)
#for sampler 1: supplementary material: sensitivity, specifictiy and precision
s1_250mig_pss_80_90 <- cbind(all_250mig_s1_80_data2[,c(2:4,5:7)],
all_250mig_s1_90_data2[,c(2:4,5:7)])
s1_250mig_pss_80_90["Sensitivity"] <- paste(round(s1_250mig_pss_80_90$sensitivity80, 3),
round(s1_250mig_pss_80_90$sensitivity90, 3), sep = "/")
s1_250mig_pss_80_90["Specificity"] <- paste(round(s1_250mig_pss_80_90$specificity80, 3),
round(s1_250mig_pss_80_90$specificity90, 3), sep = "/")
s1_250mig_pss_80_90["Precision"] <- paste(round(s1_250mig_pss_80_90$precision80, 3),
round(s1_250mig_pss_80_90$precision90, 3), sep = "/")
final_table_250mig_pss_s1 <- s1_250mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_250mig_pss_s1["perc"] <- as.factor(as.numeric(final_table_250mig_pss_s1$perc) * 100)
final_table_250mig_pss_s1["param"] <- ifelse(final_table_250mig_pss_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_250mig_pss_s1["Parameter/Tree/Perc."] <- paste(final_table_250mig_pss_s1$param,
final_table_250mig_pss_s1$code,
final_table_250mig_pss_s1$perc,
sep = "/ ")
print(xtable(final_table_250mig_pss_s1[c(7,4:6)]), include.rownames=FALSE)
#500mig
s1_500mig_pss_80_90 <- cbind(all_500mig_s1_80_data2[,c(2:4,5:7)],
all_500mig_s1_90_data2[,c(2:4,5:7)])
s1_500mig_pss_80_90["Sensitivity"] <- paste(round(s1_500mig_pss_80_90$sensitivity80, 3),
round(s1_500mig_pss_80_90$sensitivity90, 3), sep = "/")
s1_500mig_pss_80_90["Specificity"] <- paste(round(s1_500mig_pss_80_90$specificity80, 3),
round(s1_500mig_pss_80_90$specificity90, 3), sep = "/")
s1_500mig_pss_80_90["Precision"] <- paste(round(s1_500mig_pss_80_90$precision80, 3),
round(s1_500mig_pss_80_90$precision90, 3), sep = "/")
final_table_500mig_pss_s1 <- s1_500mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_500mig_pss_s1["perc"] <- as.factor(as.numeric(final_table_500mig_pss_s1$perc) * 100)
final_table_500mig_pss_s1["param"] <- ifelse(final_table_500mig_pss_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_500mig_pss_s1["Parameter/Tree/Perc."] <- paste(final_table_500mig_pss_s1$param,
final_table_500mig_pss_s1$code,
final_table_500mig_pss_s1$perc,
sep = "/ ")
print(xtable(final_table_500mig_pss_s1[c(7,4:6)]), include.rownames=FALSE)
#750mig
s1_750mig_pss_80_90 <- cbind(all_750mig_s1_80_data2[,c(2:4,5:7)],
all_750mig_s1_90_data2[,c(2:4,5:7)])
s1_750mig_pss_80_90["Sensitivity"] <- paste(round(s1_750mig_pss_80_90$sensitivity80, 3),
round(s1_750mig_pss_80_90$sensitivity90, 3), sep = "/")
s1_750mig_pss_80_90["Specificity"] <- paste(round(s1_750mig_pss_80_90$specificity80, 3),
round(s1_750mig_pss_80_90$specificity90, 3), sep = "/")
s1_750mig_pss_80_90["Precision"] <- paste(round(s1_750mig_pss_80_90$precision80, 3),
round(s1_750mig_pss_80_90$precision90, 3), sep = "/")
final_table_750mig_pss_s1 <- s1_750mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_750mig_pss_s1["perc"] <- as.factor(as.numeric(final_table_750mig_pss_s1$perc) * 100)
final_table_750mig_pss_s1["param"] <- ifelse(final_table_750mig_pss_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_750mig_pss_s1["Parameter/Tree/Perc."] <- paste(final_table_750mig_pss_s1$param,
final_table_750mig_pss_s1$code,
final_table_750mig_pss_s1$perc,
sep = "/ ")
print(xtable(final_table_750mig_pss_s1[c(7,4:6)]), include.rownames=FALSE)
#for sampler 2: supplementary material: sensitivity, specifictiy and precision ----
s2_250mig_pss_80_90 <- cbind(all_250mig_s2_80_data2[,c(2:4,5:7)],
all_250mig_s2_90_data2[,c(2:4,5:7)])
s2_250mig_pss_80_90["Sensitivity"] <- paste(round(s2_250mig_pss_80_90$sensitivity80, 3),
round(s2_250mig_pss_80_90$sensitivity90, 3), sep = "/")
s2_250mig_pss_80_90["Specificity"] <- paste(round(s2_250mig_pss_80_90$specificity80, 3),
round(s2_250mig_pss_80_90$specificity90, 3), sep = "/")
s2_250mig_pss_80_90["Precision"] <- paste(round(s2_250mig_pss_80_90$precision80, 3),
round(s2_250mig_pss_80_90$precision90, 3), sep = "/")
final_table_250mig_pss_s2 <- s2_250mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_250mig_pss_s2["perc"] <- as.factor(as.numeric(final_table_250mig_pss_s2$perc) * 100)
final_table_250mig_pss_s2["param"] <- ifelse(final_table_250mig_pss_s2$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_250mig_pss_s2["Parameter/Tree/Perc."] <- paste(final_table_250mig_pss_s2$param,
final_table_250mig_pss_s2$code,
final_table_250mig_pss_s2$perc,
sep = "/ ")
print(xtable(final_table_250mig_pss_s2[c(7,4:6)]), include.rownames=FALSE)
#500mig
s2_500mig_pss_80_90 <- cbind(all_500mig_s2_80_data2[,c(2:4,5:7)],
all_500mig_s2_90_data2[,c(2:4,5:7)])
s2_500mig_pss_80_90["Sensitivity"] <- paste(round(s2_500mig_pss_80_90$sensitivity80, 3),
round(s2_500mig_pss_80_90$sensitivity90, 3), sep = "/")
s2_500mig_pss_80_90["Specificity"] <- paste(round(s2_500mig_pss_80_90$specificity80, 3),
round(s2_500mig_pss_80_90$specificity90, 3), sep = "/")
s2_500mig_pss_80_90["Precision"] <- paste(round(s2_500mig_pss_80_90$precision80, 3),
round(s2_500mig_pss_80_90$precision90, 3), sep = "/")
final_table_500mig_pss_s2 <- s2_500mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_500mig_pss_s2["perc"] <- as.factor(as.numeric(final_table_500mig_pss_s2$perc) * 100)
final_table_500mig_pss_s2["param"] <- ifelse(final_table_500mig_pss_s2$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_500mig_pss_s2["Parameter/Tree/Perc."] <- paste(final_table_500mig_pss_s2$param,
final_table_500mig_pss_s2$code,
final_table_500mig_pss_s2$perc,
sep = "/ ")
print(xtable(final_table_500mig_pss_s2[c(7,4:6)]), include.rownames=FALSE)
#750mig
s2_750mig_pss_80_90 <- cbind(all_750mig_s2_80_data2[,c(2:4,5:7)],
all_750mig_s2_90_data2[,c(2:4,5:7)])
s2_750mig_pss_80_90["Sensitivity"] <- paste(round(s2_750mig_pss_80_90$sensitivity80, 3),
round(s2_750mig_pss_80_90$sensitivity90, 3), sep = "/")
s2_750mig_pss_80_90["Specificity"] <- paste(round(s2_750mig_pss_80_90$specificity80, 3),
round(s2_750mig_pss_80_90$specificity90, 3), sep = "/")
s2_750mig_pss_80_90["Precision"] <- paste(round(s2_750mig_pss_80_90$precision80, 3),
round(s2_750mig_pss_80_90$precision90, 3), sep = "/")
final_table_750mig_pss_s2 <- s2_750mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_750mig_pss_s2["perc"] <- as.factor(as.numeric(final_table_750mig_pss_s2$perc) * 100)
final_table_750mig_pss_s2["param"] <- ifelse(final_table_750mig_pss_s2$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_750mig_pss_s2["Parameter/Tree/Perc."] <- paste(final_table_750mig_pss_s2$param,
final_table_750mig_pss_s2$code,
final_table_750mig_pss_s2$perc,
sep = "/ ")
print(xtable(final_table_750mig_pss_s2[c(7,4:6)]), include.rownames=FALSE)
#for main text
s1_250mig_pss_80_90 <- cbind(all_250mig_s1_80_data2[,c(2:4,5:7)],
all_250mig_s1_90_data2[,c(2:4,5:7)])
s1_250mig_pss_80_90["Sensitivity"] <- paste(round(s1_250mig_pss_80_90$sensitivity80, 3),
round(s1_250mig_pss_80_90$sensitivity90, 3), sep = "/")
s1_250mig_pss_80_90["Specificity"] <- paste(round(s1_250mig_pss_80_90$specificity80, 3),
round(s1_250mig_pss_80_90$specificity90, 3), sep = "/")
s1_250mig_pss_80_90["Precision"] <- paste(round(s1_250mig_pss_80_90$precision80, 3),
round(s1_250mig_pss_80_90$precision90, 3), sep = "/")
final_table_250mig_pss_s1 <- s1_250mig_pss_80_90[c(3:1,39:37,57:55,6:4,42:40,60:58),c(1:3,13:15)]
final_table_250mig_pss_s1["perc"] <- as.factor(as.numeric(final_table_250mig_pss_s1$perc) * 100)
final_table_250mig_pss_s1["param"] <- ifelse(final_table_250mig_pss_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_250mig_pss_s1["Parameter/Tree/Perc."] <- paste(final_table_250mig_pss_s1$param,
final_table_250mig_pss_s1$code,
final_table_250mig_pss_s1$perc,
sep = "/ ")
print(xtable(final_table_250mig_pss_s1[c(7,4:6)]), include.rownames=FALSE)
#500mig
thednainus/HIVepisimAnalysis documentation built on Sept. 21, 2023, 7:32 a.m.
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#generate tables for paper
library(xtable)
source("Analyses/consensus_sequences/TP_TN_FP_FN_estimation.R")
source("Analyses/consensus_sequences/TP_TN_FP_FN_estimation_threshold90.R")
#Table for total pairs for consensus sequences
#for main text
#merge data for threshold of 80% and 90% for migration probability of 1/500
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_500mig_s1_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_500mig_s1_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s1_500mig_80_90 <- cbind(all_500mig_s1_80_data2[,c(2:4,8:13)],
all_500mig_s1_90_data2[,c(2:4,8:13)])
s1_500mig_80_90["TP"] <- paste(s1_500mig_80_90$total_TP80, s1_500mig_80_90$total_TP90, sep = "/")
s1_500mig_80_90["FP"] <- paste(s1_500mig_80_90$total_FP80, s1_500mig_80_90$total_FP90, sep = "/")
s1_500mig_80_90["TN"] <- paste(s1_500mig_80_90$total_TN80, s1_500mig_80_90$total_TN90, sep = "/")
s1_500mig_80_90["FN"] <- paste(s1_500mig_80_90$total_FN80, s1_500mig_80_90$total_FN90, sep = "/")
s1_500mig_80_90["Total"] <- paste(s1_500mig_80_90$total80, s1_500mig_80_90$total90, sep = "/")
s1_500mig_80_90["TP wiw"] <- paste(s1_500mig_80_90$total_wiw_within_TP80, s1_500mig_80_90$total_wiw_within_TP90, sep = "/")
final_table_500mig_s1 <- s1_500mig_80_90[c(1:6,37:42,55:60),c(1:3,19:22,24)]
final_table_500mig_s1 <- final_table_500mig_s1[order(final_table_500mig_s1$param,final_table_500mig_s1$perc),]
final_table_500mig_s1 <- final_table_500mig_s1[order(final_table_500mig_s1$code, decreasing = TRUE),]
final_table_500mig_s1["perc"] <- as.factor(as.numeric(final_table_500mig_s1$perc) * 100)
final_table_500mig_s1["param"] <- ifelse(final_table_500mig_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_500mig_s1["Parameter/Tree/Perc."] <- paste(final_table_500mig_s1$param,
final_table_500mig_s1$code,
final_table_500mig_s1$perc,
sep = "/ ")
print(xtable(final_table_500mig_s1[c(9,4:8)]), include.rownames=FALSE)
# sampler 1: for supplementary material ----
#merge data for threshold of 80% and 90% for migration probability of 1/250
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_250mig_s1_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_250mig_s1_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s1_250mig_80_90 <- cbind(all_250mig_s1_80_data2[,c(2:4,8:13)],
all_250mig_s1_90_data2[,c(2:4,8:13)])
s1_250mig_80_90["TP"] <- paste(s1_250mig_80_90$total_TP80, s1_250mig_80_90$total_TP90, sep = "/")
s1_250mig_80_90["FP"] <- paste(s1_250mig_80_90$total_FP80, s1_250mig_80_90$total_FP90, sep = "/")
s1_250mig_80_90["TN"] <- paste(s1_250mig_80_90$total_TN80, s1_250mig_80_90$total_TN90, sep = "/")
s1_250mig_80_90["FN"] <- paste(s1_250mig_80_90$total_FN80, s1_250mig_80_90$total_FN90, sep = "/")
s1_250mig_80_90["Total"] <- paste(s1_250mig_80_90$total80, s1_250mig_80_90$total90, sep = "/")
s1_250mig_80_90["TP wiw"] <- paste(s1_250mig_80_90$total_wiw_within_TP80, s1_250mig_80_90$total_wiw_within_TP90, sep = "/")
s1_250mig_80_90["perc"] <- as.factor(as.numeric(s1_250mig_80_90$perc) * 100)
s1_250mig_80_90["param"] <- ifelse(s1_250mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s1_250mig_80_90["Parameter/Tree/Perc."] <- paste(s1_250mig_80_90$param,
s1_250mig_80_90$code,
s1_250mig_80_90$perc,
sep = "/ ")
final_table_250mig_s1 <- s1_250mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_250mig_s1), include.rownames=FALSE)
#for supplementary material
#merge data for threshold of 80% and 90% for migration probability of 1/500
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_500mig_s1_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_500mig_s1_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s1_500mig_80_90 <- cbind(all_500mig_s1_80_data2[,c(2:4,8:13)],
all_500mig_s1_90_data2[,c(2:4,8:13)])
s1_500mig_80_90["TP"] <- paste(s1_500mig_80_90$total_TP80, s1_500mig_80_90$total_TP90, sep = "/")
s1_500mig_80_90["FP"] <- paste(s1_500mig_80_90$total_FP80, s1_500mig_80_90$total_FP90, sep = "/")
s1_500mig_80_90["TN"] <- paste(s1_500mig_80_90$total_TN80, s1_500mig_80_90$total_TN90, sep = "/")
s1_500mig_80_90["FN"] <- paste(s1_500mig_80_90$total_FN80, s1_500mig_80_90$total_FN90, sep = "/")
s1_500mig_80_90["Total"] <- paste(s1_500mig_80_90$total80, s1_500mig_80_90$total90, sep = "/")
s1_500mig_80_90["TP wiw"] <- paste(s1_500mig_80_90$total_wiw_within_TP80, s1_500mig_80_90$total_wiw_within_TP90, sep = "/")
s1_500mig_80_90["perc"] <- as.factor(as.numeric(s1_500mig_80_90$perc) * 100)
s1_500mig_80_90["param"] <- ifelse(s1_500mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s1_500mig_80_90["Parameter/Tree/Perc."] <- paste(s1_500mig_80_90$param,
s1_500mig_80_90$code,
s1_500mig_80_90$perc,
sep = "/ ")
final_table_500mig_s1 <- s1_500mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_500mig_s1), include.rownames=FALSE)
#for supplementary material
#merge data for threshold of 80% and 90% for migration probability of 1/750
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_750mig_s1_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_750mig_s1_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s1_750mig_80_90 <- cbind(all_750mig_s1_80_data2[,c(2:4,8:13)],
all_750mig_s1_90_data2[,c(2:4,8:13)])
s1_750mig_80_90["TP"] <- paste(s1_750mig_80_90$total_TP80, s1_750mig_80_90$total_TP90, sep = "/")
s1_750mig_80_90["FP"] <- paste(s1_750mig_80_90$total_FP80, s1_750mig_80_90$total_FP90, sep = "/")
s1_750mig_80_90["TN"] <- paste(s1_750mig_80_90$total_TN80, s1_750mig_80_90$total_TN90, sep = "/")
s1_750mig_80_90["FN"] <- paste(s1_750mig_80_90$total_FN80, s1_750mig_80_90$total_FN90, sep = "/")
s1_750mig_80_90["Total"] <- paste(s1_750mig_80_90$total80, s1_750mig_80_90$total90, sep = "/")
s1_750mig_80_90["TP wiw"] <- paste(s1_750mig_80_90$total_wiw_within_TP80, s1_750mig_80_90$total_wiw_within_TP90, sep = "/")
s1_750mig_80_90["perc"] <- as.factor(as.numeric(s1_750mig_80_90$perc) * 100)
s1_750mig_80_90["param"] <- ifelse(s1_750mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s1_750mig_80_90["Parameter/Tree/Perc."] <- paste(s1_750mig_80_90$param,
s1_750mig_80_90$code,
s1_750mig_80_90$perc,
sep = "/ ")
final_table_750mig_s1 <- s1_750mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_750mig_s1), include.rownames=FALSE)
# sampler 2: for supplementary material ----
#merge data for threshold of 80% and 90% for migration probability of 1/250
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_250mig_s2_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_250mig_s2_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s2_250mig_80_90 <- cbind(all_250mig_s2_80_data2[,c(2:4,8:13)],
all_250mig_s2_90_data2[,c(2:4,8:13)])
s2_250mig_80_90["TP"] <- paste(s2_250mig_80_90$total_TP80, s2_250mig_80_90$total_TP90, sep = "/")
s2_250mig_80_90["FP"] <- paste(s2_250mig_80_90$total_FP80, s2_250mig_80_90$total_FP90, sep = "/")
s2_250mig_80_90["TN"] <- paste(s2_250mig_80_90$total_TN80, s2_250mig_80_90$total_TN90, sep = "/")
s2_250mig_80_90["FN"] <- paste(s2_250mig_80_90$total_FN80, s2_250mig_80_90$total_FN90, sep = "/")
s2_250mig_80_90["Total"] <- paste(s2_250mig_80_90$total80, s2_250mig_80_90$total90, sep = "/")
s2_250mig_80_90["TP wiw"] <- paste(s2_250mig_80_90$total_wiw_within_TP80, s2_250mig_80_90$total_wiw_within_TP90, sep = "/")
s2_250mig_80_90["perc"] <- as.factor(as.numeric(s2_250mig_80_90$perc) * 100)
s2_250mig_80_90["param"] <- ifelse(s2_250mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s2_250mig_80_90["Parameter/Tree/Perc."] <- paste(s2_250mig_80_90$param,
s2_250mig_80_90$code,
s2_250mig_80_90$perc,
sep = "/ ")
final_table_250mig_s2 <- s2_250mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_250mig_s2), include.rownames=FALSE)
#for supplementary material
#merge data for threshold of 80% and 90% for migration probability of 1/500
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_500mig_s2_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_500mig_s2_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s2_500mig_80_90 <- cbind(all_500mig_s2_80_data2[,c(2:4,8:13)],
all_500mig_s2_90_data2[,c(2:4,8:13)])
s2_500mig_80_90["TP"] <- paste(s2_500mig_80_90$total_TP80, s2_500mig_80_90$total_TP90, sep = "/")
s2_500mig_80_90["FP"] <- paste(s2_500mig_80_90$total_FP80, s2_500mig_80_90$total_FP90, sep = "/")
s2_500mig_80_90["TN"] <- paste(s2_500mig_80_90$total_TN80, s2_500mig_80_90$total_TN90, sep = "/")
s2_500mig_80_90["FN"] <- paste(s2_500mig_80_90$total_FN80, s2_500mig_80_90$total_FN90, sep = "/")
s2_500mig_80_90["Total"] <- paste(s2_500mig_80_90$total80, s2_500mig_80_90$total90, sep = "/")
s2_500mig_80_90["TP wiw"] <- paste(s2_500mig_80_90$total_wiw_within_TP80, s2_500mig_80_90$total_wiw_within_TP90, sep = "/")
s2_500mig_80_90["perc"] <- as.factor(as.numeric(s2_500mig_80_90$perc) * 100)
s2_500mig_80_90["param"] <- ifelse(s2_500mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s2_500mig_80_90["Parameter/Tree/Perc."] <- paste(s2_500mig_80_90$param,
s2_500mig_80_90$code,
s2_500mig_80_90$perc,
sep = "/ ")
final_table_500mig_s2 <- s2_500mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_500mig_s2), include.rownames=FALSE)
#for supplementary material
#merge data for threshold of 80% and 90% for migration probability of 1/750
#individuals per year
#total pairs classified as TP, FP, TN, and FN
names(all_750mig_s2_80_data2)[c(5:13)] <- c("precision80",
"sensitivity80",
"specificity80",
"total_TP80",
"total_FP80",
"total_TN80",
"total_FN80",
"total80",
"total_wiw_within_TP80")
names(all_750mig_s2_90_data2)[c(5:13)] <- c("precision90",
"sensitivity90",
"specificity90",
"total_TP90",
"total_FP90",
"total_TN90",
"total_FN90",
"total90",
"total_wiw_within_TP90")
s2_750mig_80_90 <- cbind(all_750mig_s2_80_data2[,c(2:4,8:13)],
all_750mig_s2_90_data2[,c(2:4,8:13)])
s2_750mig_80_90["TP"] <- paste(s2_750mig_80_90$total_TP80, s2_750mig_80_90$total_TP90, sep = "/")
s2_750mig_80_90["FP"] <- paste(s2_750mig_80_90$total_FP80, s2_750mig_80_90$total_FP90, sep = "/")
s2_750mig_80_90["TN"] <- paste(s2_750mig_80_90$total_TN80, s2_750mig_80_90$total_TN90, sep = "/")
s2_750mig_80_90["FN"] <- paste(s2_750mig_80_90$total_FN80, s2_750mig_80_90$total_FN90, sep = "/")
s2_750mig_80_90["Total"] <- paste(s2_750mig_80_90$total80, s2_750mig_80_90$total90, sep = "/")
s2_750mig_80_90["TP wiw"] <- paste(s2_750mig_80_90$total_wiw_within_TP80, s2_750mig_80_90$total_wiw_within_TP90, sep = "/")
s2_750mig_80_90["perc"] <- as.factor(as.numeric(s2_750mig_80_90$perc) * 100)
s2_750mig_80_90["param"] <- ifelse(s2_750mig_80_90$param == "1067",
"Combination 1 ", "Combination 2 ")
s2_750mig_80_90["Parameter/Tree/Perc."] <- paste(s2_750mig_80_90$param,
s2_750mig_80_90$code,
s2_750mig_80_90$perc,
sep = "/ ")
final_table_750mig_s2 <- s2_750mig_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(25,19:22,24)]
print(xtable(final_table_750mig_s2), include.rownames=FALSE)
#for sampler 1: supplementary material: sensitivity, specifictiy and precision
s1_250mig_pss_80_90 <- cbind(all_250mig_s1_80_data2[,c(2:4,5:7)],
all_250mig_s1_90_data2[,c(2:4,5:7)])
s1_250mig_pss_80_90["Sensitivity"] <- paste(round(s1_250mig_pss_80_90$sensitivity80, 3),
round(s1_250mig_pss_80_90$sensitivity90, 3), sep = "/")
s1_250mig_pss_80_90["Specificity"] <- paste(round(s1_250mig_pss_80_90$specificity80, 3),
round(s1_250mig_pss_80_90$specificity90, 3), sep = "/")
s1_250mig_pss_80_90["Precision"] <- paste(round(s1_250mig_pss_80_90$precision80, 3),
round(s1_250mig_pss_80_90$precision90, 3), sep = "/")
final_table_250mig_pss_s1 <- s1_250mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_250mig_pss_s1["perc"] <- as.factor(as.numeric(final_table_250mig_pss_s1$perc) * 100)
final_table_250mig_pss_s1["param"] <- ifelse(final_table_250mig_pss_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_250mig_pss_s1["Parameter/Tree/Perc."] <- paste(final_table_250mig_pss_s1$param,
final_table_250mig_pss_s1$code,
final_table_250mig_pss_s1$perc,
sep = "/ ")
print(xtable(final_table_250mig_pss_s1[c(7,4:6)]), include.rownames=FALSE)
#500mig
s1_500mig_pss_80_90 <- cbind(all_500mig_s1_80_data2[,c(2:4,5:7)],
all_500mig_s1_90_data2[,c(2:4,5:7)])
s1_500mig_pss_80_90["Sensitivity"] <- paste(round(s1_500mig_pss_80_90$sensitivity80, 3),
round(s1_500mig_pss_80_90$sensitivity90, 3), sep = "/")
s1_500mig_pss_80_90["Specificity"] <- paste(round(s1_500mig_pss_80_90$specificity80, 3),
round(s1_500mig_pss_80_90$specificity90, 3), sep = "/")
s1_500mig_pss_80_90["Precision"] <- paste(round(s1_500mig_pss_80_90$precision80, 3),
round(s1_500mig_pss_80_90$precision90, 3), sep = "/")
final_table_500mig_pss_s1 <- s1_500mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_500mig_pss_s1["perc"] <- as.factor(as.numeric(final_table_500mig_pss_s1$perc) * 100)
final_table_500mig_pss_s1["param"] <- ifelse(final_table_500mig_pss_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_500mig_pss_s1["Parameter/Tree/Perc."] <- paste(final_table_500mig_pss_s1$param,
final_table_500mig_pss_s1$code,
final_table_500mig_pss_s1$perc,
sep = "/ ")
print(xtable(final_table_500mig_pss_s1[c(7,4:6)]), include.rownames=FALSE)
#750mig
s1_750mig_pss_80_90 <- cbind(all_750mig_s1_80_data2[,c(2:4,5:7)],
all_750mig_s1_90_data2[,c(2:4,5:7)])
s1_750mig_pss_80_90["Sensitivity"] <- paste(round(s1_750mig_pss_80_90$sensitivity80, 3),
round(s1_750mig_pss_80_90$sensitivity90, 3), sep = "/")
s1_750mig_pss_80_90["Specificity"] <- paste(round(s1_750mig_pss_80_90$specificity80, 3),
round(s1_750mig_pss_80_90$specificity90, 3), sep = "/")
s1_750mig_pss_80_90["Precision"] <- paste(round(s1_750mig_pss_80_90$precision80, 3),
round(s1_750mig_pss_80_90$precision90, 3), sep = "/")
final_table_750mig_pss_s1 <- s1_750mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_750mig_pss_s1["perc"] <- as.factor(as.numeric(final_table_750mig_pss_s1$perc) * 100)
final_table_750mig_pss_s1["param"] <- ifelse(final_table_750mig_pss_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_750mig_pss_s1["Parameter/Tree/Perc."] <- paste(final_table_750mig_pss_s1$param,
final_table_750mig_pss_s1$code,
final_table_750mig_pss_s1$perc,
sep = "/ ")
print(xtable(final_table_750mig_pss_s1[c(7,4:6)]), include.rownames=FALSE)
#for sampler 2: supplementary material: sensitivity, specifictiy and precision ----
s2_250mig_pss_80_90 <- cbind(all_250mig_s2_80_data2[,c(2:4,5:7)],
all_250mig_s2_90_data2[,c(2:4,5:7)])
s2_250mig_pss_80_90["Sensitivity"] <- paste(round(s2_250mig_pss_80_90$sensitivity80, 3),
round(s2_250mig_pss_80_90$sensitivity90, 3), sep = "/")
s2_250mig_pss_80_90["Specificity"] <- paste(round(s2_250mig_pss_80_90$specificity80, 3),
round(s2_250mig_pss_80_90$specificity90, 3), sep = "/")
s2_250mig_pss_80_90["Precision"] <- paste(round(s2_250mig_pss_80_90$precision80, 3),
round(s2_250mig_pss_80_90$precision90, 3), sep = "/")
final_table_250mig_pss_s2 <- s2_250mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_250mig_pss_s2["perc"] <- as.factor(as.numeric(final_table_250mig_pss_s2$perc) * 100)
final_table_250mig_pss_s2["param"] <- ifelse(final_table_250mig_pss_s2$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_250mig_pss_s2["Parameter/Tree/Perc."] <- paste(final_table_250mig_pss_s2$param,
final_table_250mig_pss_s2$code,
final_table_250mig_pss_s2$perc,
sep = "/ ")
print(xtable(final_table_250mig_pss_s2[c(7,4:6)]), include.rownames=FALSE)
#500mig
s2_500mig_pss_80_90 <- cbind(all_500mig_s2_80_data2[,c(2:4,5:7)],
all_500mig_s2_90_data2[,c(2:4,5:7)])
s2_500mig_pss_80_90["Sensitivity"] <- paste(round(s2_500mig_pss_80_90$sensitivity80, 3),
round(s2_500mig_pss_80_90$sensitivity90, 3), sep = "/")
s2_500mig_pss_80_90["Specificity"] <- paste(round(s2_500mig_pss_80_90$specificity80, 3),
round(s2_500mig_pss_80_90$specificity90, 3), sep = "/")
s2_500mig_pss_80_90["Precision"] <- paste(round(s2_500mig_pss_80_90$precision80, 3),
round(s2_500mig_pss_80_90$precision90, 3), sep = "/")
final_table_500mig_pss_s2 <- s2_500mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_500mig_pss_s2["perc"] <- as.factor(as.numeric(final_table_500mig_pss_s2$perc) * 100)
final_table_500mig_pss_s2["param"] <- ifelse(final_table_500mig_pss_s2$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_500mig_pss_s2["Parameter/Tree/Perc."] <- paste(final_table_500mig_pss_s2$param,
final_table_500mig_pss_s2$code,
final_table_500mig_pss_s2$perc,
sep = "/ ")
print(xtable(final_table_500mig_pss_s2[c(7,4:6)]), include.rownames=FALSE)
#750mig
s2_750mig_pss_80_90 <- cbind(all_750mig_s2_80_data2[,c(2:4,5:7)],
all_750mig_s2_90_data2[,c(2:4,5:7)])
s2_750mig_pss_80_90["Sensitivity"] <- paste(round(s2_750mig_pss_80_90$sensitivity80, 3),
round(s2_750mig_pss_80_90$sensitivity90, 3), sep = "/")
s2_750mig_pss_80_90["Specificity"] <- paste(round(s2_750mig_pss_80_90$specificity80, 3),
round(s2_750mig_pss_80_90$specificity90, 3), sep = "/")
s2_750mig_pss_80_90["Precision"] <- paste(round(s2_750mig_pss_80_90$precision80, 3),
round(s2_750mig_pss_80_90$precision90, 3), sep = "/")
final_table_750mig_pss_s2 <- s2_750mig_pss_80_90[c(3:1,9:7,15:13,21:19,27:25,33:31,39:37,
45:43,51:49,57:55,6:4, 12:10,18:16,
24:22,30:28,36:34,42:40,48:46,54:52,
60:58),c(1:3,13:15)]
final_table_750mig_pss_s2["perc"] <- as.factor(as.numeric(final_table_750mig_pss_s2$perc) * 100)
final_table_750mig_pss_s2["param"] <- ifelse(final_table_750mig_pss_s2$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_750mig_pss_s2["Parameter/Tree/Perc."] <- paste(final_table_750mig_pss_s2$param,
final_table_750mig_pss_s2$code,
final_table_750mig_pss_s2$perc,
sep = "/ ")
print(xtable(final_table_750mig_pss_s2[c(7,4:6)]), include.rownames=FALSE)
#for main text
s1_250mig_pss_80_90 <- cbind(all_250mig_s1_80_data2[,c(2:4,5:7)],
all_250mig_s1_90_data2[,c(2:4,5:7)])
s1_250mig_pss_80_90["Sensitivity"] <- paste(round(s1_250mig_pss_80_90$sensitivity80, 3),
round(s1_250mig_pss_80_90$sensitivity90, 3), sep = "/")
s1_250mig_pss_80_90["Specificity"] <- paste(round(s1_250mig_pss_80_90$specificity80, 3),
round(s1_250mig_pss_80_90$specificity90, 3), sep = "/")
s1_250mig_pss_80_90["Precision"] <- paste(round(s1_250mig_pss_80_90$precision80, 3),
round(s1_250mig_pss_80_90$precision90, 3), sep = "/")
final_table_250mig_pss_s1 <- s1_250mig_pss_80_90[c(3:1,39:37,57:55,6:4,42:40,60:58),c(1:3,13:15)]
final_table_250mig_pss_s1["perc"] <- as.factor(as.numeric(final_table_250mig_pss_s1$perc) * 100)
final_table_250mig_pss_s1["param"] <- ifelse(final_table_250mig_pss_s1$param == "1067",
"Combination 1 ", "Combination 2 ")
final_table_250mig_pss_s1["Parameter/Tree/Perc."] <- paste(final_table_250mig_pss_s1$param,
final_table_250mig_pss_s1$code,
final_table_250mig_pss_s1$perc,
sep = "/ ")
print(xtable(final_table_250mig_pss_s1[c(7,4:6)]), include.rownames=FALSE)
#500mig
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