How can editors and reviewers detect data manipulation?
The image manipulations reported on Retraction Watch are most of the time naive collages of gel photographs or spectrograms. They get caught, among other things, because repeating patterns in the noise appear on closer inspection, or linear disruption of the noise are visible, see this.

For 1D data, the case you mention, there is the Benford's law and other statistical tests that can indicate potential manipulation of data. It usually relies on human beings preferring certain digits over others, even unconsciously, thus generating data that has a non-random variability.

Also, many journals ask for graphs to be submitted in vector format, which means you are actually sending the data points, and not just a rendered figure. Things like editing out a few data points to smooth a curve will be apparent. 

Now, to the best of my knowledge publishers and, even less so, reviewers don't systematically screen for these things, they only do so if they have suspicions, because the scientific publishing process is based on good faith. But if the paper gets any sort of attention it will get caught by post publication review.

Don't fabricate/manipulate data. It's adding unwanted noise to an already noisy signal, it's dishonest towards your coworkers, the people who fund you, the publisher and the readership, and it will ruin your career.