I have this dataframe called mydf
where I have three principal covariates (PCA.1,PCA.2, PCA.3). I want to get the 3d distance matrix and get the shortest euclidean distance between all the compared Samples
. In another dataframe called myref
, I have some known identity of Samples
and some unknown
samples. By calculating the shortest euclidean distance from mydf, I want to assign the known Identity
to the unknown samples. Can someone please help me get this done.
mydf
mydf <- structure(list(Sample = c("1", "2", "4", "5", "6", "7", "8",
"9", "10", "12"), PCA.1 = c(0.00338, -0.020373, -0.019842, -0.019161,
-0.019594, -0.019728, -0.020356, 0.043339, -0.017559, -0.020657
), PCA.2 = c(0.00047, -0.010116, -0.011532, -0.011582, -0.013245,
-0.011751, -0.010299, -0.005801, -0.01, -0.011334), PCA.3 = c(-0.008787,
0.001412, 0.003751, 0.00371, 0.004242, 0.003738, 0.000592, -0.037229,
0.004307, 0.00339)), .Names = c("Sample", "PCA.1", "PCA.2", "PCA.3"
), row.names = c(NA, 10L), class = "data.frame")
myref
myref<- structure(list(Sample = c("1", "2", "4", "5", "6", "7", "8",
"9", "10", "12"), Identity = c("apple", "unknown", "ball", "unknown",
"unknown", "car", "unknown", "cat", "unknown", "dog")), .Names = c("Sample",
"Identity"), row.names = c(NA, 10L), class = "data.frame")