CODEWITHSUNDEEP
r
Anon
Anon

Reputation: 1547

R: How to create boolean variables for dataframe?

I want to create is.mut (mutants) and is.wt (wild-type) boolean variables, where samples are either is.mut or is.wt.

Mutants are defined as:

data.table::setDT(res.gs)[grepl("^[^0]", n_mutated_group1), ]

Wild-types are defined as anything not mutant.

My attempt at creating boolean variables resulted in FALSE for all is.mut.

# Labels 
is.mut <- (data.table::setDT(res.gs)[grepl("^[^0]", n_mutated_group1), ])=="TRUE"
is.wt <- (data.table::setDT(res.gs)[grepl("^[^0]", n_mutated_group1), ])=="FALSE"

> dput(res.gs)
structure(list(Hugo_Symbol = c("AKAP9", "AKAP9", "ERCC2", "ERCC2", 
"HECTD1", "HECTD1", "HERC1", "HERC1", "KMT2C", "KMT2C", "MACF1", 
"MACF1", "MROH2B", "MROH2B"), Missense_Mutation = c(9L, 9L, 9L, 
9L, 6L, 6L, 8L, 8L, 19L, 19L, 5L, 5L, 5L, 5L), Nonsense_Mutation = c(0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L), Splice_Site = c(0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, 1L), total = c(9L, 
9L, 9L, 9L, 6L, 6L, 8L, 8L, 20L, 20L, 6L, 6L, 6L, 6L), MutatedSamples = c(6L, 
6L, 9L, 9L, 6L, 6L, 6L, 6L, 8L, 8L, 6L, 6L, 6L, 6L), AlteredSamples = c(6L, 
6L, 9L, 9L, 6L, 6L, 6L, 6L, 8L, 8L, 6L, 6L, 6L, 6L), Group1 = c("Non-Responder", 
"Responder", "Non-Responder", "Responder", "Non-Responder", "Responder", 
"Non-Responder", "Responder", "Non-Responder", "Responder", "Non-Responder", 
"Responder", "Non-Responder", "Responder"), Group2 = c("Rest", 
"Rest", "Rest", "Rest", "Rest", "Rest", "Rest", "Rest", "Rest", 
"Rest", "Rest", "Rest", "Rest", "Rest"), n_mutated_group1 = c("0 of 25", 
"6 of 25", "0 of 25", "9 of 25", "0 of 25", "6 of 25", "0 of 25", 
"6 of 25", "1 of 25", "7 of 25", "0 of 25", "6 of 25", "0 of 25", 
"6 of 25"), n_mutated_group2 = c("6 of 25", "0 of 25", "9 of 25", 
"0 of 25", "6 of 25", "0 of 25", "6 of 25", "0 of 25", "7 of 25", 
"1 of 25", "6 of 25", "0 of 25", "6 of 25", "0 of 25"), p_value = c(0.022289766970618, 
0.022289766970618, 0.00163083541184905, 0.00163083541184905, 
0.022289766970618, 0.022289766970618, 0.022289766970618, 0.022289766970618, 
0.0487971536957187, 0.0487971536957187, 0.022289766970618, 0.022289766970618, 
0.022289766970618, 0.022289766970618), OR = c(0, Inf, 0, Inf, 
0, Inf, 0, Inf, 0.111488645279478, 8.96952328636894, 0, Inf, 
0, Inf), OR_low = c(0, 1.33358819424024, 0, 2.56647319276964, 
0, 1.33358819424024, 0, 1.33358819424024, 0.00228988507629356, 
1.0079479819766, 0, 1.33358819424024, 0, 1.33358819424024), OR_high = c(0.749856668137133, 
Inf, 0.38963976043749, Inf, 0.749856668137133, Inf, 0.749856668137133, 
Inf, 0.992114690322592, 436.703138665198, 0.749856668137133, 
Inf, 0.749856668137133, Inf), fdr = c(0.248902397838568, 0.248902397838568, 
0.109265972593886, 0.109265972593886, 0.248902397838568, 0.248902397838568, 
0.248902397838568, 0.248902397838568, 0.467058471087594, 0.467058471087594, 
0.248902397838568, 0.248902397838568, 0.248902397838568, 0.248902397838568
)), row.names = c(NA, -14L), class = "data.frame")

Desired output (example): TRUE FALSE TRUE TRUE FALSE TRUE

Upvotes: 0

Views: 114

Answers (1)

jpiversen
jpiversen

Reputation: 3212

The command grepl("^[^0]", n_mutated_group1) will return either TRUE or FALSE. These are boolean values, not strings.

Say, if it returns TRUE, then it doesn't make sense to compare TRUE == "TRUE", as this will always return FALSE since "TRUE" is a string.

Thus, to get the result you are looking for, just simplify your code to:

is.mut <- (data.table::setDT(res.gs)[grepl("^[^0]", n_mutated_group1), ])
is.wt <- (data.table::setDT(res.gs)[!grepl("^[^0]", n_mutated_group1), ])

Upvotes: 1

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