README.mkdn 2.2 KB

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  1. # Human globin protocol stats
  2. This is a pair of spreadsheets summarizing the globin-reducing
  3. properties of an experimental RNA-seq protocol.
  4. - [`method-select.xlsx`](method-select.xlsx) shows the results for
  5. several different methods of globin reduction. The most important
  6. column is "Non-HB", which represents the fraction of total reads
  7. that map to non-globin genes.
  8. - [`concentration-select.xlsx`](concentration-select.xlsx) shows the
  9. results of selecting the best globin blocking method and optimizing
  10. the concentration of blockers as well as the number of
  11. hybridizations.
  12. # Cyno globin plots
  13. This is a series of example plots for evaluation of a similar globin
  14. reduction protocol that was designed for cynomolgus monkeys.
  15. - [`BCVplots.pdf`](BCVplots.pdf) and [`corrplot.pdf`](corrplot.pdf)
  16. show, respectively, that the biological coefficient of variation is
  17. not increased, and the sample-to-sample correlation is not
  18. decreased, by the globin reduction protocol.
  19. - [`cyno-vs-hg19.pdf`](cyno-vs-hg19.pdf) shows excellent correlation
  20. between total read counts on the cyno and human genomes, indicating
  21. that the cyno annotation is reasonably complete.
  22. - [`pval-comparisons.pdf`](pval-comparisons.pdf) shows the comparison
  23. between p-values from edgeR, limma-voom, and DESeq2 on the exact
  24. same differential expression test. Surprisingly, despite the
  25. significant algorithmic differences, edgeR and limma are in quite
  26. close agreement. DESeq2 id overly liberal because it does not
  27. account for the negative estimation bias in negative-binomial
  28. dispersions.
  29. # Publication plots
  30. These are the figures from an upcoming publication on the developed
  31. globin blocking method.
  32. - [Figure 1](figure1 - globin-fractions.pdf): Globin blocking (GB)
  33. substantially increases yield and consistency of non-globin reads.
  34. - [Figure 2](figure2 - aveLogCPM-colored.pdf): GB lowers the noise
  35. floor and increases the distance between noise floor and signal.
  36. - [Figrue 3](figure3 - detection.pdf): GB allows detection of more
  37. genes at any abundance threshold.
  38. - [Figure 4](figure4 - maplot-colored.pdf): GB has small but
  39. systematic effects on other genes' measured expression levels.
  40. - [Figure 5](figure5 - corrplot.pdf): GB Significantly increases
  41. correlation between libraries.