View outlier trajectory plots

Here we clear our figure and then display the outliers in original order or what one might consider to be the unsorted native ordering of the dataset. This ordering would be the same ordering as any other unsorted plot that one might chose to create.

fig.clf()
pcaginsu.plotPCNOutlierRowsInOriginalColumnOrder(1)
show()

In this case we see the same data but sorted by the difference of mean "high" and mean "low" expression. "High" vectors are defined as those that started high, while low vectors are (as one might guess) are the ones that started off as the most negative of all the values in the selected principal component.

fig.clf()
pcaginsu.plotPCNOutlierRowsInSigOrder(1)
show()