  In the last decade we have seen an enormous increase in the size and quality
of spectroscopic galaxy surveys, both at low and high redshift. New statistical
techniques to analyse large portions of galaxy spectra are now finding favour
over traditional index based methods. Here we will review a new robust and
iterative Principal Component Analysis (PCA) algorithm, which solves several
common issues with classic PCA. Application to the 4000AA break region of
galaxies in the VIMOS VLT Deep Survey (VVDS) and Sloan Digital Sky Survey
(SDSS) gives new high signal-to-noise ratio spectral indices easily
interpretable in terms of recent star formation history. In particular, we
identify a sample of post-starburst galaxies at z~0.7 and z~0.07. We quantify
for the first time the importance of post-starburst galaxies, consistent with
being descendants of gas-rich major mergers, for building the red sequence.
Finally, we present a comparison with new low and high redshift "mock
spectroscopic surveys" derived from a Millennium Run semi-analytic model.
