Goal: Compare the average volume of the major protrusion for untreated cells and CK666 treated cells.
Got all the major protrusion volumes
untreated.largest.prot = c(c14_protrusions_rv2$V3, c15_protrusions_rv$V3, c10_protrusions_rv2$V3, c12_protrusions_rv$V3)
Found the mean and the standard dev
Note: for setting all NAs to 0:
x[is.na(x)] <- 0
The average volume of the major protrusion is higher, but also has a very large standard deviation.
Goal: To see if there is a correlation between the protrusion parameters matrix and the math of the cells using linear regression.
DMSO treated cells (in order): cell 14, cell 15, cell 12, cell 10
CK666 treated cells (in order): cell 43 ,cell 48 , cell 55 , cell 53
variables: Count, largest protusion volume, total protustion volume, protrusion fraction, largest protrusion length, largest protrusion angle, and total protrusion angle.
Dependent value (y): derivative using savitzky-golay
To get rid of rows without Y values
I did this because the smoothing window on the sg filter leaves a lot of blank values for the derivative.
Results: all the parameters were significant except largest protrusion angle, and total angles. The largest protrusion length is only significant for the first few fits.
Dependent value (y): curve method
Dependent value (y): bi-modal with cutoff (ie, is the cell turning or not turning?)
To do next:
add more cells to the training set
write function to find average turning point prediction