# making table data sets
library(dplyr)
library(tidyr)
library(data.table)
library(MorpheusData)
#############benchmark 1
dat <- read.table(text=
"
GeneID D_1 T_1 D_2 T_2 D_3 T_3 D_4 T_4 D_5 T_5 D_6 T_6 D_7 T_7 D_8 T_8
A2M 8876.5 8857.9 10246.8 9453.9 6279.6 3846.5 8735.3 6609.9 7732.95 2452.4 8705.2 6679.0 7510.5 4318.3 8957.7 4092.4
ABL1 2120.8 1664.9 2525.0 1546.4 1993.0 1713.7 1849.7 1761.9 2297.7 2462.5 2698.2 1975.8 2480.3 1694.6 2471.0 1784.1
ACP1 1266.6 1347.1 910.95 725.1 1327.6 1589.5 1175.0 1086.9 1187.3 1065.15 1080.0 1048.2 1213.8 1337.9 831.5 814.1
", header=T)
write.csv(dat, "data-raw/r84_input1.csv", row.names=FALSE)
df_out <- read.table(text=
"
col1 A2M ABL1 ACP1
D 67044.55 18435.7 8992.75
T 46310.3 14603.9 9013.95
", header=T)
##df_out = dat %>% gather(var, val, -1) %>% filter(val!=0) %>% select(-3)
#%>% arrange(order_id)
write.csv(df_out, "data-raw/r84_output1.csv", row.names=FALSE)
r84_output1 <- read.csv("data-raw/r84_output1.csv", check.names = FALSE)
fctr.cols <- sapply(r84_output1, is.factor)
int.cols <- sapply(r84_output1, is.integer)
r84_output1[, fctr.cols] <- sapply(r84_output1[, fctr.cols], as.character)
r84_output1[, int.cols] <- sapply(r84_output1[, int.cols], as.numeric)
save(r84_output1, file = "data/r84_output1.rdata")
r84_input1 <- read.csv("data-raw/r84_input1.csv", check.names = FALSE)
fctr.cols <- sapply(r84_input1, is.factor)
int.cols <- sapply(r84_input1, is.integer)
r84_input1[, fctr.cols] <- sapply(r84_input1[, fctr.cols], as.character)
r84_input1[, int.cols] <- sapply(r84_input1[, int.cols], as.numeric)
save(r84_input1, file = "data/r84_input1.rdata")
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