Most of the genomics data sets are in the form of genomic intervals associated with a score. That means mostly the data will be in table format with columns denoting chromosome, start positions, end positions, strand and score. One of the popular formats is BED format used primarily by UCSC genome browser but most other genome browsers and tools will support BED format. We have all the annotation data in BED format. In R, you can easily read tabular format data with read.table() function.
enh.df <- read.table("../data/subset.enhancers.hg18.bed", header = FALSE) # read enhancer marker BED file
cpgi.df <- read.table("../data/subset.cpgi.hg18.bed", header = FALSE) # read CpG island BED file
# check first lines to see how the data looks like
head(enh.df)
## V1 V2 V3 V4 V5 V6 V7 V8 V9
## 1 chr20 266275 267925 . 1000 . 9.11 13.17 -1
## 2 chr20 287400 294500 . 1000 . 10.53 13.02 -1
## 3 chr20 300500 302500 . 1000 . 9.10 13.39 -1
## 4 chr20 330400 331800 . 1000 . 6.39 13.51 -1
## 5 chr20 341425 343400 . 1000 . 6.20 12.99 -1
## 6 chr20 437975 439900 . 1000 . 6.31 13.52 -1
head(cpgi.df)
## V1 V2 V3 V4
## 1 chr20 195575 195851 CpG:_28
## 2 chr20 207789 208148 CpG:_32
## 3 chr20 219055 219437 CpG:_33
## 4 chr20 225831 227155 CpG:_135
## 5 chr20 252826 256323 CpG:_286
## 6 chr20 275376 276977 CpG:_116
You can save your data by writing it to disk as a text file. A data frame or matrix can be written out by using write.table() function. Now let us write out cpgi.df, we will write it out as a tab-separated file, pay attention to the arguments.
write.table(cpgi.df,file="cpgi.txt",quote=FALSE,
row.names=FALSE,col.names=FALSE,sep="\t")
You can save your R objects directly into a file using save() and saveRDS() and load them back in with load() and readRDS(). By using these functions you can save any R object whether or not they are in data frame or matrix classes.
save(cpgi.df, enh.df, file = "mydata.RData")
load("mydata.RData")
# saveRDS() can save one object at a type
saveRDS(cpgi.df, file = "cpgi.rds")
x = readRDS("cpgi.rds")
head(x)
## V1 V2 V3 V4
## 1 chr20 195575 195851 CpG:_28
## 2 chr20 207789 208148 CpG:_32
## 3 chr20 219055 219437 CpG:_33
## 4 chr20 225831 227155 CpG:_135
## 5 chr20 252826 256323 CpG:_286
## 6 chr20 275376 276977 CpG:_116
One important thing is that with save() you can save many objects at a time and when they are loaded into memory with load() they retain their variable names. For example, in the above code when you use load("mydata.RData") in a fresh R session, an object names “cpg.df” will be created. That means you have to figure out what name you gave it to the objects before saving them. On the contrary to that, when you save an object by saveRDS() and read by readRDS() the name of the object is not retained, you need to assign the output of readRDS() to a new variable (“x” in the above code chunk).