Intensities by individual ID and plate

Last updated: 2017-12-11

Code version: 960abf5

Summary

Previously, we saw a wide range of variability across plates in DAPI intensities, and to a lesser extent, in Green and Red intensities. Here we look at variation between individuals and see that there’s significantly smaller variation between individuals in all three measurements. In addition, in the across-plate results, the DAPI distributions have similar shape across plates and a possible mean-shift between distributions. While, the shape of the green/red distributions are not consistent across plates, possibly reflecting differences in proprotion of samples expressing red/green fluorescent proteins.

For normalization approach, we can use mean correction approaches for DAPI. While, for Green/Red, it’s less obvious what would be a good approach. Let me try qsmooth and see….

Load data

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ints <- readRDS(file="/project2/gilad/joycehsiao/fucci-seq/data/intensity.rds")

By plate

\(~\)

ggplot(ints, aes(x=gfp.mean.log10sum,col = as.factor(plate))) + 
  geom_density(alpha = .5, cex = .7) + 
  labs(title = "Green (log10 pixel sum) by plate",
       x="Green channel log10 pixel sum", y = "Density") + theme_gray()

ggplot(ints, aes(x=rfp.mean.log10sum,col = as.factor(plate))) + 
  geom_density(alpha = .5, cex = .7) + 
  labs(title = "Red (log10 pixel sum) by plate",
       x="Red channel log10 pixel sum", y = "Density") + theme_gray()

ggplot(ints, aes(x=dapi.mean.log10sum,col = as.factor(plate))) + 
  geom_density(alpha = .5, cex = .7) + 
  labs(title = "DAPI (log10 pixel sum) by plate",
       x="DAPI channel log10 pixel sum", y = "Density") + theme_gray()

By individual