Binary R heatmap still displays gradient

Question

I'm trying to plot a heatmap for a matrix of binary data (11 x ~1500) in R.

heatmap(y, col = hmcols);

the matrix 'y' looks like this

[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13]
[1,]    0    0    0    0    1    1    1    1    1     1     1     1     1
[2,]    0    0    1    0    0    1    0    0    0     0     0     0     1
[3,]    0    0    0    0    0    1    1    1    1     0     0     1     1 ...etc...

I'm using the default distance and clustering functions, but for some reason my heatmap displays a gradient of color. I've tried to use the binary distance function as well, although a similar gradied occurs. Is this a lack of similarity in samples due to the distance between each sample? Here is an image of the heatmap:

https://www.dropbox.com/s/jz1r41lhnrkisvz/Rplots.pdf

I feel like this is due to my lack of understanding of exactly how the default distance and clustering functions reorder data. How can I interpret these results?

Answer 1

As @Joran point out, the scale argument is the one to go with:

(Note: I reduced dimensionality and generated random data since you did not provide your full set)

The colors are chosen by col, if you want simple black and white you can do col = c("black", "white"), but you can also make things more interesting:

x <- matrix(sample(c(0, 1), 15*15, replace = TRUE), nrow = 15)
heatmap(x, scale = "none", Rowv = NA, Colv = NA, col = cm.colors(2), main = "HeatMap Example")