apply returns same value for all rows

I have a large dataframe and need to run t-tests on different combinations of columns (based on the column name) and ultimately get back the p-values for each row. However, when I ran the apply function on my dataframe, I get the same p-value for every single row.

Everyone says to use apply(df,1,function(x){t.test()} and I have done that, but I get the same result for each row.

I’ve simplified my code a bit here, I’ll ultimately be using grep for fetching column indices but putting in numbers has given me the same result.

Using the example data below:

> apply(test2,1, function(x) {t.test(test2[1:10], test2[11:14])$p.value})
    ABCC1     ABCC4     ABCG2      ABI1      ABL1 
0.6789077 0.6789077 0.6789077 0.6789077 0.6789077 

Example data:

test2 <- structure(list(a = c(-0.250175512841836, -0.598132059346627, 
2.36944314821787, 0.712175496367779, 0.554244500083983), b = c(-0.393946411778548, 
-1.98106284210261, -0.837040169410122, -0.375424411534213, -0.105374520148301
), c = c(0.567833193559877, 0.136364370754434, 2.50245414535438, 
-0.088430913069187, 0.893158718942739), d = c(-0.459274650062501, 
0.744994126390252, -1.28861019919615, 0.33548964839072, -0.0093089669382681
), e = c(-1.0203598678196, 0.0567193103158077, -0.311685225886462, 
-0.0739549362904639, -0.0492254321641561), f = c(-0.238227233511192, 
0.578013461518793, 0.741419593172567, -0.298619983451011, 0.224712996269695
), g = c(-0.706469879467227, 0.0437438246019302, 1.47410341528079, 
-0.150703626309354, -0.42885770081535), h = c(-0.619451795584007, 
-1.12320908559054, 2.90373539528014, 0.00703583668484074, 0.765518916949785
), i = c(-0.387644599880135, 0.176923681687052, 0.739332511375104, 
0.0960565706257697, 0.209166609859509), j = c(-0.123146246400315, 
-0.259771309210745, -1.31764790409046, -0.321380288291338, 0.688189220698862
), k = c(-0.277023010101889, 0.486542707980388, -0.621224972880764, 
0.350319335163238, 0.0708201926811306), l = c(-0.284338994897708, 
-0.58392166777083, 1.1654879751381, -0.288421241758868, -0.0324290411715858
), m = c(0.253071717309849, 0.288787254692779, -1.36850678881865, 
0.161053825472205, -0.316171510458368), n = c(0.308290287689747, 
-0.191408294902337, 0.824243786561308, -0.222951918876576, 0.277780358948823
)), row.names = c("ABCC1", "ABCC4", "ABCG2", "ABI1", "ABL1"), class = "data.frame")

>Solution :

Try:

apply(test2,1, function(x) {t.test(x[1:10], x[11:14])$p.value})