The title is a mouthful, but here is what it amounts to:
Under a proposal distribution using an independent chain, the probability of jumping to point $x$ is independent of the current position $y$ of the chain. Thus $q(x; y) = g(x)$. Now suppose I choose an asymmetric continuous distribution for $g(y)$, for example log-normal. In such cases my acceptance function $\rho(x;y)$ becomes
$\rho(x;y)=\min \left( \frac{f(x)}{f(y)}*\frac{q(y|x)}{q(x|y)},1 \right)$
Now what I don't understand is how to compute $q(y|x)=P(x \rightarrow y) = P(y)$ and $q(x|y)=P(y \rightarrow x) = P(x)$. Since $y$ and $x$ are drawn from continuous densities, their probabilities are zero. I must be wrong somewhere in my reasoning, but do not know where. Anyone can clarify?