I want to perform student's t-test on the res.gs dataframe, where the samples are either is.mut or is.wt.

# Students' T-test without KMT2C gene
is.mut <- grepl('^[^0]', nokmt2c.res.gs$n_mutated_group1)
is.wt <- !grepl('^[^0]', nokmt2c.res.gs$n_mutated_group1)

t.test.all.genes <- function(x,s1,s2) {
  x <- as.numeric(x)
  x1 <- x[s1]
  x2 <- x[s2]
  x1 <- as.numeric(x1)
  x2 <- as.numeric(x2)
  t.out <- t.test(x1,x2, alternative="two.sided",var.equal=T)
  out <- as.numeric(t.out$p.value)
  return(out)
}
rawp <- apply(nokmt2c.res.gs, 1, t.test.all.genes, s1=is.mut, s2=is.wt)

Traceback:

Error in if (stderr < 10 * .Machine$double.eps * max(abs(mx), abs(my))) stop("data are essentially constant") : 
  missing value where TRUE/FALSE needed
In addition: Warning messages:
1: In FUN(newX[, i], ...) : NAs introduced by coercion
2: In FUN(newX[, i], ...) : NAs introduced by coercion
Called from: t.test.default(x1, x2, alternative = "two.sided", var.equal = T)

Data

    > 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")