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We will perform absorbance checks, compile the data, and then sort out the best program for normalization. Probably, we will normalize to around 10 ng/ul. 1 nM is the minimum library concentration for a NovaSeq run. From the data here, 1.44 nM ~ 4 ng/ul. We would like to operate under a larger margin of error.

Is there a relationship between reads and qPCR?

Code Block
languager
ggplot(LRIIIReads, aes(NgPerUl, mean, color=plate, shape=plate))+
  geom_point(show.legend = TRUE)+
  geom_smooth(method='lm', formula= y~x)+
  stat_regline_equation(label.y = 125, aes(label = ..eq.label..)) +
  stat_regline_equation(label.y = 100, aes(label = ..rr.label..))+
  facet_wrap(~plate)
Image Added

Excluding the Mock Community samples, there is a strong relationship between absorbance and qPCR. The odd MC results may be a result of the small Data Set, their larger than average contribution to the data set, and their very low relative complexity.

Files:

View file
nameLRIIIanalysis.pdf
View file
nameLRIIIanalysis.Rmd
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nameMC_MB_Comparison.csv
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nameLRIIIfiltermergestats.csv
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nameLRIII.txt
View file
name5LVD5_Col123.csv
View file
name5DG5_COL456.csv

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