CODEWITHSUNDEEP
rdataframefor-loopif-statementconditional-statements
KLM117
KLM117

Reputation: 467

A for loop using a double conditional

I'm currently trying to create a dual conditional, where, if the Cancer type (Indication) and Gene (Genes) of my data frame "mockup" both appear in another data frame called "cpg", then a new column in the mockup table has either a "yes" if both conditions are met, and a "no" if not. To illustrate this:

The mockup table has:

Indication Genes
Acute Myeloid Leukemia TP53
Acute Myeloid Leukemia GNAQ

And the cpg dataframe has:

Cancer Type Gene
Acute Myeloid Leukemia TP53
Acute Myeloid Leukemia ATM

I would like to produce a mockup table that looks like this (based on the cpg data):

Indication Genes Hotspot?
Acute Myeloid Leukemia TP53 Yes
Acute Myeloid Leukemia GNAQ No

So far I've tried (and failed) to make a for loop with a conditional to create a vector, with the hopes of then appending this vector as a new column:

hotspot <- c()
for (i in 1:nrow(mockup)){
  if ((mockup$Genes[i] == cpg$Gene && mockup$Indication[i] == cpg$`Cancer Type`)){
    hotspot[i] <- print("yes")
    } else {
      hotspot[i] <- print("no")
    }
}

unique(hotspot)

As always, any help would really be appreciated!

Upvotes: 0

Views: 37

Answers (1)

AnilGoyal
AnilGoyal

Reputation: 26238

Is this required? For loops in R, as R is already vectorised, are generally avoidable.

  • Base R version
mockup <- read.table(text = 'Indication Genes
"Acute Myeloid Leukemia"    TP53
"Acute Myeloid Leukemia"    GNAQ', header = T)

cpg <- read.table(text = "Cancer_Type   Gene
'Acute Myeloid Leukemia'    TP53
'Acute Myeloid Leukemia'    ATM", header = T)

mockup$hotspot <- apply(mockup, 1, function(x) c('No','Yes')[(all(x %in% as.matrix(cpg)))

mockup
              Indication Genes hotspot
1 Acute Myeloid Leukemia  TP53     Yes
2 Acute Myeloid Leukemia  GNAQ      No

dplyr pipe friendly version

library(dplyr)

mockup %>% rowwise() %>%
  mutate(hotspot = c('No', 'Yes')[+(all(cur_data() %in% as.matrix(cpg))+1)])
#> # A tibble: 2 x 3
#> # Rowwise: 
#>   Indication             Genes hotspot
#>   <chr>                  <chr> <chr>  
#> 1 Acute Myeloid Leukemia TP53  Yes    
#> 2 Acute Myeloid Leukemia GNAQ  No

Upvotes: 2

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