R

Matrix related

• combine data

missCount <- rnorm(100, mean=2, sd=0.5)
missPercent <- missCount/(colCount-2)
missDataStatus <- rbind(missCount,missPercent)
missDataStatus.2 <- cbind(missCount,missPercent)

• get row names and col names

getOriData <- read.table("modified_data",header=T,sep="\t")
rowName <- rownames(getOriData)
colName <- colnames(getOriData)

• row and column counts

getOriData <- read.table("modified_data",header=T,sep="\t")
rowCount <- nrow(getOriData)
colCount <- ncol(getOriData)

• type transformation into matrix

# method.1
X <- c(1,2,3)
Y <- c(4,5,6)
Z <- as.matrix(rbind(X,Y))

# method.2
new_matrx <- matrix(
  rnorm(100, mean=4, sd=1),
  nrow = 10,
  ncol = 10
)

• transpose matrix by " t() "

transZ <- t(Z)

Loop

Branch

• if else

if() { ... }
else if() { ... }
else { ... }

• try catch

tryCatch(
    res <- as.numeric(input),
    warning = function(w) { ... },
    error = function(e) { ... },
    finally { ... }
)

System Interaction

• system parameters

# trailingOnly = TRUE/FALSE to show all default parameters
sysArgs <- commandArgs(trailingOnly = TRUE)

• start from index 1

for(i in 1:length(sysArgs)) { ... }

Set theory

File I/O

• write a text file

sink("out.txt", append = TRUE)
cat( ... )
sink()