Data from 140722 m2a + trc experiment

Josh's notes on this data:

There is a file in there that decodes the sample identities from the fcs
file names as to construct type, treatment condition, time point etc.
Also, there is file to translate the fcs colum names to which antibody I
used (ie cPARP is the 405 channel, etc) Some samples listed did not get
analysed, for a very convoluted set of reasons, but there is enough
there to get the flavor.

random thoughts:

The fcs files are for the "p2" group of cells, these have already been
gated on scatter channels to select for singlet cells.  I left the side
scatter pretty wide on these, and so there are a small percentage of
outliers in the side scatter dimension.  These are just really big
cells. for simplicity I gated them out above 20000, removing the top
3.5% of cells by size.

You'll see that the best cParp +/- divide  includes the side scatter
dimension.

The facs signal is more akin to the integrated fluorescence than the
average fluorescence, so size effects should mattter if what we are
interested in is the concentration.  Sabrina saw that all the steady
state parameters she looked at by facs (bcl-2 bid, bax) were positively
correlated, which probably means that cell size effects are large
relative to normal distributions of protein values in a population.   I
have wondered what is out there in terms of using side scatter info to
do some sort of size correction, but have not really looked into it, and
at this level of resolution, it may not matter anyway.

To get a sense for how stable the cherry protein was over time during
TRAIL/CHX, I looked at the D60E construct, which did not die, but
otherwise experienced the TRAIL pathway activation.  The distribution of
cherry value takes a sort of bumpy shape in these lines, so I looked for
a single value that would align the chy distribution profiles for the t
= i time point with that of the t=0 profile.  This turned out to be near
a 1% per hour loss in cherry value, which I compensated for throughout
my first round of analysis.  This did not work as well for early time
points, so the signal loss may not happen smoothly.   A better way to do
this would be good.

I used the t=o data set for each construct to arrive at the best
relationship between Cherry and Venus signals at "steady state". I
discarded outliers far off the diagonal for this purpose ( only a few).
Then I use the relationship between average Venus signal for the TALEN
standard and "1X" or 2.7uM to get the BidVenus axes in concentration
units.

There are a lot of BidKO cell in these populations, and the distribution
of the BidKOs (negatives for chy and Venus) spills over into the low
expressers range, limiting the lower limit of confidently calling
something Cherry+ or Venus+.  In the future, I will likely sort these
lines to remove some of the true negatives, and hopefully gain
confidence in the lower cherry numbers.