mat<-read.csv("mat.csv")
sub<-c(123,132)

set<- subset(mat, mat$V2 %in% sub)
set[,7]<-set[,7]+1

# download and read in your file from dropbox
tf <- tempfile()
library(httr)
csvpage <- GET( "https://dl.dropbox.com/u/22681355/mat.csv" )
writeBin(content(csvpage, "raw"), tf )

# import the data into R
mat <- read.csv( tf )

# note read.csv creates a data frame not a matrix
class( mat )

# create your sub object
sub <- c(123,132)

# subset the matrix..

# show all rows where V2 is equal to any of the contents of sub
mat[ mat$V2 %in% sub , ]

# access only the V7 column for rows where V2 is equal to the contents of sub
mat[ mat$V2 %in% sub , 'V7' ]

# overwrite the V7 column with MISSING
# for rows where V2 is equal to the contents of sub
mat[ mat$V2 %in% sub , 'V7' ] <- NA

# OR

# overwrite the V7 column with the value of V2 (which matched something in sub)
# for rows where V2 is equal to the contents of sub
mat[ mat$V2 %in% sub , 'V7' ] <- mat[ mat$V2 %in% sub , 'V2' ]

# OR

# overwrite the V7 column with itself plus one
# for rows where V2 is equal to the contents of sub
mat[ mat$V2 %in% sub , 'V7' ] <- mat[ mat$V2 %in% sub , 'V7' ] + 1

mat[7] <- mat[7] + mat$V2 %in% sub

mat["V7"] <- mat["V7"] + mat$V2 %in% sub