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Bioconductor Preprocessing Overview for Salmo Data Sets

Learn about preprocessing techniques using Bioconductor for Salmo array data, including color flip design, background correction, MA plots, normalization methods, and statistical analysis like SAM, CyberT, and Volcano plots.

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Bioconductor Preprocessing Overview for Salmo Data Sets

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  1. Preprocessing Bioconductor

  2. Overview • Data set Salmo, color flip design Name Cy5 Cy3 FileName 2004012211 array1 self1 self2 2004012211.txt 2004012212 array2 self2 self1 2004012212.txt RG$printer $ngrid.r [1] 12 $ngrid.c [1] 4 $nspot.r [1] 17 $nspot.c [1] 17

  3. Red background

  4. Green background

  5. Plot raw data Raw data cartesian coordinates Raw data log scale Data background corrected

  6. MA plot before normalisation

  7. MA per print tip before normalisation

  8. MA after print tip normalisation

  9. MA after print tip normalisation

  10. Box plot Between array normalisation not essential

  11. SWIRL DATASET

  12. Between array normalisation essential

  13. Volcano plot Log oddsL Log(p/(1-p))

  14. SALMO array • 6 replica’s (6 normalised ratios) Design > Salmo.cl <-rep(c(1),6) > Salmo.cl [1] 1 1 1 1 1 1 SAM Paired,

  15. SAM

  16. SAM

  17. CyberT

  18. Results CyberT Mn: mean ratio # obs: number of ratios available to calculate the statistics SD: standard deviation on the ratio estimates T, p calculated t and p value that indicate the significance of the measurement

  19. Results CyberT

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