Counts and coverage stats

files

 [1] "EPI-103_CG.output.txt" "EPI-104_CG.output.txt" "EPI-111_CG.output.txt" "EPI-113_CG.output.txt" "EPI-119_CG.output.txt" "EPI-120_CG.output.txt"
 [7] "EPI-127_CG.output.txt" "EPI-128_CG.output.txt" "EPI-135_CG.output.txt" "EPI-136_CG.output.txt" "EPI-143_CG.output.txt" "EPI-145_CG.output.txt"

sharedLoci$EPI_103_Meth <- rowSums(EPI_103_CG_output$`Watson METH`, EPI_103_CG_output$`Crick METH`, na.rm =TRUE)

Error in rowSums(EPI_103_CG_output$`Watson METH`, EPI_103_CG_output$`Crick METH`,  : 
  'x' must be an array of at least two dimensions

nrow(sharedLoci)

[1] 5016318

Number of loci that have data for all samples.

nrow(sharedLoci2)

[1] 611458

Mean total coverage by sample

samp.means

EPI_103_TotCov  EPI-104TotCov  EPI-111TotCov  EPI-113TotCov  EPI-119TotCov  EPI-120TotCov  EPI-127TotCov  EPI-128TotCov  EPI-135TotCov  EPI-136TotCov 
      5.891979       8.631464       8.360712       7.761975       7.805427       7.539605       6.963849       7.800521       8.961659       8.498826 
 EPI-143TotCov  EPI-145TotCov 
      6.360996       7.835375 

Mean coverage

mean(samp.means)

[1] 7.701032

Then, iff we decide to restrict coverage to only that which is greater than 10x, we’re down to 18,000ish records.

nrow(sharedLoci3)

[1] 17823

Our coverage means increase a lot, with a total coverage mean of 48.

mean(samp.means2)

[1] 48.2429

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