DECONV DREAM Challenege 2020 (5)

library(gridExtra)
library(ggplot2)
a3$type<-"glmnet200"
a4$type<-"glmnet250"
a5$type<-"glmnet350"
a6$type<-"glmnet500"
x1$type<-"svr200"
x2$type<-"svr250"
x3$type<-"svr300"
x4$type<-"svr500"

z4$type<-"pls500"
z3$type<-"pls350"
z2$type<-"pls250"
z1$type<-"pls200"

heatmap <-rbind(a3,a4,a5,a6,
                
                x1,x2,x3,x4,
                z1,z2,z3,z4)

 

Heatmap per cell (Pearson)

#library(ggplotify)
#par(mfrow=c(2,1))
pattern="DS"

heatmap %>% group_by(type,cells) %>%  summarise(pearson=mean(pearson)) %>% reshape2::acast(type ~cells) %>% as.matrix() %>% d3heatmap::d3heatmap(colors = "Blues")

Heatmap per cell rnaseq (Pearson)

heatmap %>% filter(datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>% group_by(type,cells) %>%  summarise(pearson=mean(pearson)) %>% reshape2::acast(type ~cells) %>% as.matrix() %>% d3heatmap::d3heatmap(colors = "Blues")

Heatmap per cell (Spearman)

heatmap %>% group_by(type,cells) %>% summarise(spearman=mean(spearman)) %>% reshape2::acast(type ~cells) %>% as.matrix() %>% d3heatmap::d3heatmap(colors = "Reds")

Heatmap per cell rnaseq (Spearman)

heatmap  %>% filter(datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>% group_by(type,cells) %>% summarise(spearman=mean(spearman)) %>% reshape2::acast(type ~cells) %>% as.matrix() %>% d3heatmap::d3heatmap(colors = "Reds")

Heatmap per dataset (Pearson)

#library(ggplotify)
#par(mfrow=c(2,1))
pattern="DS"

heatmap %>% group_by(type,datasets) %>%  summarise(pearson=mean(pearson)) %>% reshape2::acast(type ~datasets) %>% as.matrix() %>% d3heatmap::d3heatmap(colors = "Blues")

Heatmap per dataset rnaseq (Pearson)

heatmap %>% filter(datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>% group_by(type,datasets) %>%  summarise(pearson=mean(pearson)) %>% reshape2::acast(type ~datasets) %>% as.matrix() %>% d3heatmap::d3heatmap(colors = "Blues")

Heatmap per dataset (Spearman)

heatmap %>% group_by(type,datasets) %>% summarise(spearman=mean(spearman)) %>% reshape2::acast(type ~datasets) %>% as.matrix() %>% d3heatmap::d3heatmap(colors = "Reds")

Heatmap per dataset rnaseq (Spearman)

heatmap  %>% filter(datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>% group_by(type,datasets) %>% summarise(spearman=mean(spearman)) %>% reshape2::acast(type ~datasets) %>% as.matrix() %>% d3heatmap::d3heatmap(colors = "Reds")

a3 [glmnet200] Results for glmnet 200 features over 20000 (RF2)

filename<-"./devcon_challenge.glmnet_results_noscale_rf_selected_features_200_20000_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
a3<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
a3

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

a4 [glmnet250] Results for glmnet 250 features over 20000 (RF2)

filename<-"./devcon_challenge.glmnet_results_noscale_rf_selected_features_250_20000_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
a4<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
a4

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

a5 [glmnet350] Results for glmnet 350 features over 20000 (RF2)

filename<-"./devcon_challenge.glmnet_results_noscale_rf_selected_features_350_20000_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
a5<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
a5

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

a6 [glmnet500] Results for glmnet 500 features over 20000 (RF2)

filename<-"./devcon_challenge.glmnet_results_noscale_rf_selected_features_500_20000_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
a6<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
a6

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

NA

x1 [svr200] Results for svr radial noscale 200 features over 20000 (RF2)

filename<-"./devcon_challenge.svr_results_rf_selected_features_200_20000_noscale_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
x1<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
x1

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

x2 [svr250] Results for svr radial noscale 250 features over 20000 (RF2)

filename<-"./devcon_challenge.svr_results_rf_selected_features_250_20000_noscale_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
x2<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
x2

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

x3 [svr350] Results for svr radial noscale 350 features over 20000 (RF2)

filename<-"./devcon_challenge.svr_results_rf_selected_features_350_20000_noscale_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
x3<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
x3

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

x4 [svr500] Results for svr radial noscale 500 features over 20000 (RF2)

filename<-"./devcon_challenge.svr_results_rf_selected_features_500_20000_noscale_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
x4<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
x4

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

z4 [pls500] Results for pls 500 features (RF)

filename<-"./devcon_challenge.pls_results_rf_selected_features_500_20000_noscale_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
z4<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
z4

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

z3 [pls350] Results for pls 350 features (RF)

filename<-"./devcon_challenge.pls_results_rf_selected_features_350_20000_noscale_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
z3<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
z3

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

z2 [pls250] Results for pls 250 features (RF)

filename<-"./devcon_challenge.pls_results_rf_selected_features_250_20000_noscale_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
z2<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
z2

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

z1 [pls200] Results for pls 200 features (RF)

filename<-"./devcon_challenge.pls_results_rf_selected_features_200_20000_noscale_newmix_spearson.csv"
#readr::write_csv(RESULTS,path = filename)
z1<-readr::read_csv(filename) %>% filter(!is.na(pearson)) 
z1

readr::read_csv(filename) %>% filter(!is.na(pearson)) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

readr::read_csv(filename) %>% filter(!is.na(pearson))  %>% filter( datasets %in% c("DS446395","DS500","CIAS4","CIVA3")) %>%  summarise(pearson_mean=mean(pearson),spearman_mean=mean(spearman))

load("results_glmnet_devcon_bestmodels_fgdata_cps_20000_2_selected_features_250_test_added.rdata")
glmnet250<-results_final_models

load("results_svr_radial_devcon_bestmodels_fgdata_cps_20000_2_noscale_selected_features_200_newgama_test_added.rdata")
svr200<-results_final_models

glmnet250[['cancer']]$nzero

 s0  s1  s2  s3  s4  s5  s6  s7  s8  s9 s10 s11 s12 s13 s14 s15 s16 s17 s18 s19 s20 s21 s22 s23 s24 s25 s26 
  0   1   1   2   4   7  12  17  19  19  21  24  25  30  32  38  39  40  41  43  43  44  47  48  48  48  51 
s27 s28 s29 s30 s31 s32 s33 s34 s35 s36 s37 s38 s39 s40 s41 s42 s43 s44 s45 s46 s47 s48 s49 s50 s51 s52 s53 
 51  51  53  53  53  54  55  57  57  58  57  57  54  55  56  56  56  58  58  55  58  60  65  68  71  72  78 
s54 s55 s56 s57 s58 s59 s60 s61 s62 s63 s64 s65 s66 s67 s68 s69 s70 s71 s72 s73 s74 s75 s76 s77 s78 
 81  85  89  98 103 110 116 124 127 138 140 145 154 167 173 183 187 191 192 200 206 212 213 221 219 

svr200[['cancer']]$

Error: Incomplete expression: svr200[['cancer']]$