#Installs Packages
install.packages("bnlearn")
#Installs Packages
install.packages("bnlearn")
#Loads Library
library(bnlearn)
#Importing and Prepping
data = read.csv(file = "C:/Users/berna/OneDrive/Desktop/Fall 2019 Project/Bayesian Network Data/CCGrade100GenesAstrocytoma.csv", header = TRUE, sep=",")
bn_df = data.frame(data)
bn_df[1:101] = lapply(bn_df[1:101], as.factor)
start_time_3 = Sys.time()
bn.cv(bn_df, bn = "hc", k = 10)
end_time_3 = Sys.time()
warnings()
bn.cv(bn_df, bn = "hc", k = 10)
bn.cv(bn_df, bn = "hc", k = 10)
bn.cv(bn_df, bn = "hc", k = 10)
bn.cv(bn_df, bn = "hc", k = 10)
bn.cv(bn_df, bn = "hc", k = 10)
bn.cv(bn_df, bn = "hc", k = 5)
bn.cv(bn_df, bn = "hc", k = 5)
bn.cv(bn_df, bn = "hc", k = 5)
bn.cv(bn_df, bn = "hc", k = 5)
bn.cv(bn_df, bn = "hc", k = 5)
bn.cv(bn_df, bn = "hc", k = 15)
bn.cv(bn_df, bn = "hc", k = 15)
bn.cv(bn_df, bn = "hc", k = 15)
bn.cv(bn_df, bn = "hc", k = 15)
bn.cv(bn_df, bn = "hc", k = 15)
#Installs Packages
install.packages("bnlearn")
#Loads Library
library(bnlearn)
#Installs Packages
install.packages("bnlearn")
#Importing and Prepping
data = read.csv(file = "C:/Users/berna/OneDrive/Desktop/Fall 2019 Project/Bayesian Network Data/CCGrade100Genes.csv", header = TRUE, sep=",")
bn_df = data.frame(data)
bn_df[1:101] = lapply(bn_df[1:101], as.factor)
#Running
start_time_mmhc = Sys.time()
mmhc = mmhc(bn_df)
end_time_mmhc = Sys.time()
start_time_gs = Sys.time()
gs = gs(bn_df)
end_time_gs = Sys.time()
start_time_hc = Sys.time()
hc = hc(bn_df)
end_time_hc = Sys.time()
#Visualizing
score(mmhc)
#Visualizing
score(mmhc, bn_df)
score(gs)
score(gs, bn_df)
score(hc, bn_df)
arcs(gs)
gs
bn.fit(mmhc, bn_df)
#Visualizing
score(mmhc, bn_df)
arcs(gs)
gs
set.arc(gs, "RAVER2", "YAF2")
gs
arcs(gs)
drop.arc(gs, "YAF2", "RAVER2")
gs
arcs(gs)
gs = drop.arc(gs, "YAF2", "RAVER2")
gs
arcs(gs)
gs = gs(bn_df)
arcs(gs)
gs = set.arc(gs,"RAVER2", "YAF2")
gs
arcs(gs)
gs = set.arc(gs,"RAVER2", "YAF2")
gs = set.arc(gs,"TRPC3", "TEX261")
gs = set.arc(gs,"CYP4F8", "ZNF257")
gs = set.arc(gs,"ABCD2", "SH3TC2")
gs = set.arc(gs,"MATN3", "MRPS14")
gs
arcs(gs)
gs = set.arc(gs,"RAVER2", "YAF2")
gs = set.arc(gs,"TRPC3", "TEX261")
gs = set.arc(gs,"CYP4F8", "ZNF257")
gs = set.arc(gs,"ABCD2", "SH3TC2")
gs = set.arc(gs,"MATN3", "MRPS14")
gs = set.arc(gs,"TLL1", "MYO1D")
gs = set.arc(gs,"MSX2", "MMP10")
gs = set.arc(gs,"ZNF442", "ADRA1B")
gs = set.arc(gs,"ZNF165", "IL7")
gs
arcs(gs)
score(gs, bn_df)
score(hc, bn_df)
#Scoring the networks
score(mmhc, bn_df)
score(gs, bn_df)
score(hc, bn_df)
graphviz.plot(mmhc)
graphviz.plot(hc)
gs = gs(bn_df)
gs = set.arc(gs, "YAF2","RAVER2")
gs = set.arc(gs, "TEX261","TRPC3")
gs = set.arc(gs, "ZNF257","CYP4F8")
gs = set.arc(gs, "SH3TC2","ABCD2")
gs = set.arc(gs, "MRPS14","MATN3")
gs = set.arc(gs, "MYO1D","TLL1")
gs = set.arc(gs, "MMP10","MSX2")
gs = set.arc(gs, "ADRA1B","ZNF442")
gs = set.arc(gs, "IL7","ZNF165")
arcs(gs)
score(gs, bn_df)
gs = gs(bn_df)
gs2 = gs
gs = set.arc(gs,"RAVER2", "YAF2")
gs = set.arc(gs,"TRPC3", "TEX261")
gs = set.arc(gs,"CYP4F8", "ZNF257")
gs = set.arc(gs,"ABCD2", "SH3TC2")
gs = set.arc(gs,"MATN3", "MRPS14")
gs = set.arc(gs,"TLL1", "MYO1D")
gs = set.arc(gs,"MSX2", "MMP10")
gs = set.arc(gs,"ZNF442", "ADRA1B")
gs = set.arc(gs,"ZNF165", "IL7")
gs2 = set.arc(gs, "YAF2","RAVER2")
gs2 = set.arc(gs, "TEX261","TRPC3")
gs2 = set.arc(gs, "ZNF257","CYP4F8")
gs2 = set.arc(gs, "SH3TC2","ABCD2")
gs2 = set.arc(gs, "MRPS14","MATN3")
gs2 = set.arc(gs, "MYO1D","TLL1")
gs2 = set.arc(gs, "MMP10","MSX2")
gs2 = set.arc(gs, "ADRA1B","ZNF442")
gs2 = set.arc(gs, "IL7","ZNF165")
score(gs, bn_df)
score(gs2, bn_df)
#Installs Packages
install.packages("bnlearn")
#Loads Library
library(bnlearn)
#Importing and Prepping
data = read.csv(file = "C:/Users/berna/OneDrive/Desktop/Fall 2019 Project/Bayesian Network Data/CCGrade100GenesAstrocytoma.csv", header = TRUE, sep=",")
bn_df = data.frame(data)
bn_df[1:101] = lapply(bn_df[1:101], as.factor)
#Running
start_time_mmhc = Sys.time()
mmhc = mmhc(bn_df)
end_time_mmhc = Sys.time()
start_time_gs = Sys.time()
gs = gs(bn_df)
gs2 = gs
end_time_gs = Sys.time()
start_time_hc = Sys.time()
hc = hc(bn_df)
end_time_hc = Sys.time()
gs
arcs(gs)
gs = set.arc(gs,"HCP5", "LMOD1")
gs = set.arc(gs,"GMPPA", "CDKL1")
gs = set.arc(gs,"RAC2", "MECOM")
gs = set.arc(gs,"MAPK8IP2", "FZD2")
gs = set.arc(gs,"HCLS1", "CUTC")
gs = set.arc(gs,"ANKRD11", "LTF")
gs = set.arc(gs,"AGBL3", "PKN1")
gs = set.arc(gs,"BICC1", "CENPF")
gs
arcs(gs)
gs2 = set.arc(gs, "LMOD1","HCP5")
gs2 = set.arc(gs, "CDKL1","GMPPA")
gs2 = set.arc(gs, "MECOM","RAC2")
gs2 = set.arc(gs, "FZD2","MAPK8IP2")
gs2 = set.arc(gs, "CUTC","HCLS1")
gs2 = set.arc(gs, "LTF","ANKRD11")
gs2 = set.arc(gs, "PKN1","AGBL3")
gs2 = set.arc(gs, "CENPF","BICC1")
gs2
#Scoring the networks
score(mmhc, bn_df)
score(gs, bn_df)
score(gs2, bn_df)
score(hc, bn_df)
#Importing and Prepping
data = read.csv(file = "C:/Users/berna/OneDrive/Desktop/Fall 2019 Project/Bayesian Network Data/CCGrade100GenesGlioblastoma.csv", header = TRUE, sep=",")
#Installs Packages
install.packages("bnlearn")
#Loads Library
library(bnlearn)
#Importing and Prepping
data = read.csv(file = "C:/Users/berna/OneDrive/Desktop/Fall 2019 Project/Bayesian Network Data/CCGrade100GenesGlioblastoma.csv", header = TRUE, sep=",")
bn_df = data.frame(data)
bn_df[1:101] = lapply(bn_df[1:101], as.factor)
mmhc = mmhc(bn_df)
gs = gs(bn_df)
gs2 = gs
hc = hc(bn_df)
#Network Information
mmhc
gs
hc
graphviz.plot(hc)
#Importing and Prepping
data = read.csv(file = "C:/Users/berna/OneDrive/Desktop/Fall 2019 Project/Bayesian Network Data/CCGrade100GenesAstrocytoma.csv", header = TRUE, sep=",")
bn_df = data.frame(data)
bn_df[1:101] = lapply(bn_df[1:101], as.factor)
mmhc = mmhc(bn_df)
gs = gs(bn_df)
hc = hc(bn_df)
#Network Information
mmhc
gs
hc
#Cross Validation
#Perform cv 5 times
start_time_1 = Sys.time()
#Cross Validation
#Perform cv 5 times
start_time_1 = Sys.time()
bn.cv(bn_df, bn = "mmhc", k = 10)
end_time_1 = Sys.time()
start_time_2 = Sys.time()
bn.cv(bn_df, bn = "gs", k = 10)
end_time_2 = Sys.time()
start_time_3 = Sys.time()
bn.cv(bn_df, bn = "hc", k = 10)
end_time_3 = Sys.time()
warnings()
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "hc", k = 10)
#Importing and Prepping
data = read.csv(file = "C:/Users/berna/OneDrive/Desktop/Fall 2019 Project/Bayesian Network Data/CCGrade100GenesGlioblastoma.csv", header = TRUE, sep=",")
bn_df = data.frame(data)
bn_df[1:101] = lapply(bn_df[1:101], as.factor)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "hc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
#Importing and Prepping
data = read.csv(file = "C:/Users/berna/OneDrive/Desktop/Fall 2019 Project/Bayesian Network Data/CCGrade100GenesAstrocytoma.csv", header = TRUE, sep=",")
bn_df = data.frame(data)
bn_df[1:101] = lapply(bn_df[1:101], as.factor)
#Loads Library
library(bnlearn)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "mmhc", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
bn.cv(bn_df, bn = "gs", k = 10)
