Another thing that you might do is plot replicates.

This is a very common plot that you would do when you're doing

an interactive analysis.

So here you might want to compare, say,

you ran the same sample through the technology twice, technical replicates.

And you want to see if those two replicates produce similar results.

So here's a plot on x, the x-axis is replicate one, and

on the y-axis is replicate two.

And so here, they look very, very correlated.

So that's very good, you might see this and be comforted or think, okay,

this technology is doing very well.

There's a couple of tricky things, though, especially about plotting replicates.

So the first thing is be careful of scale.

So if you go back to this plot, 99% of the data is in the tiny little lower left-hand

corner that I've shown below to, below and to the left of the light blue line here.

So what you're seeing,

just sort of the 1% of the data that ends up getting spread out.

So one way that you can deal with this sort of tightly clustered data,

particularly for replicates, is to use transforms.

One example of a data transform is the log transform.

So if you take the log of the data and

then make the same plot, you can see they're correlated.

But now the data is much more spread out and all of the data that was super tightly

clustered down in the lower left-hand corner has been spread out a little bit.

You get a little bit better idea about what's going on in the plot.