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Differential Analysis & FDR Correction

Differential Analysis & FDR Correction . Differential Analysis Steps. Step 1: Construction of input data table in EXCEL Step 2: Save EXCEL file into tab delimited txt file Step 3: Upload data - tab delimited txt file Step 4: Choose T or U Test Step 5: Enter your email and submit

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Differential Analysis & FDR Correction

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  1. Differential Analysis& FDR Correction

  2. Differential Analysis Steps Step 1: Construction of input data table in EXCEL Step 2: Save EXCEL file into tab delimited txt file Step 3: Upload data - tab delimited txt file Step 4: Choose T or U Test Step 5: Enter your email and submit Step 6: Result interpretation: global FDR Step 7: Result interpretation: local FDR

  3. Step 1: Construction of input data table in EXCEL

  4. Step 1: • Input data format: • Cell A1: “CLASS” • 1st Column: feature names • 1st Row: sample categories. • It has to be binary, either 1 or 0 • e.g. 1 is disease, 0 is control • All other cells should be data, one sample per one column • e.g. array intensity or protein quantities

  5. EXCEL file example

  6. Step 2: Save EXCEL file into tab delimited txt file

  7. Step 3: Upload data - tab delimited txt file 1 2 3

  8. Step 3: Upload data - tab delimited txt file Input data “input.txt” selected

  9. Step 4: Choose T test or U test Choose either T or U test for analysis

  10. Step 4: T test or U test, which one to choose? • The U test is useful in the same situations as t test • U test should be used if the data are ordinal • U test is more robust to outliers • U test is more efficient • For distribution far from normal • and for sufficiently large samples

  11. To Discover Differential Features:Student’s T test or Mann Whitney U test? Student’s T test: Student’s T test is a parametric test of the null hypothesis, where the means of 2 normally distributed populations are equal.It is used when you have a nominal variable, which must only have 2 values, such as “male” and “female,” and measurement variable, and you want to compare the mean values of the measurement variable. It is a test of the null hypothesis, where the means of 2 normally distributed populations are equal. Mann-Whitney U Test: Mann-Whitney U Test is a non-parametric test that examines whether 2 sites of data could have come from the same population. It requires 2 data sets that do not need to be paired, normally distributed, or have equal numbers in each set.

  12. Step 5: Enter your email and submit Enter your email Submit

  13. Step 6: Result interpretationGlobal FDR FDR plot red line: Total Discoveries (TD) or Total Discovery rate = 1 FDR plot green line: False Discoveries (MEAN) or False Discovery Rate FDR (MEAN) FDR plot black bar line: False Discoveries (MEDIAN) or False Discovery Rate FDR (MEDIAN) FDR plot blue line: False Discoveries (95%) or False Discovery Rate FDR (95%) FDR plot dotted black line: FDR=0.05

  14. Step 6: Result interpretationGlobal FDR

  15. Step 6: How to read the gFDR plots • Commonly used global FDR cut off • 0.05 • If there are no significant features • No data points will show up below • the 0.05 dotted horizontal line

  16. Step 6: Result interpretationGlobal FDR Commonly used gFDR cutoff: 0.05 Features which satisfy global FDR < 0.05

  17. Step 6: Result interpretationGlobal FDR Commonly used gFDR cutoff: 0.05 Features which satisfy global FDR < 0.05

  18. Step 7: Result interpretationlocal FDR

  19. Step 7: How to read the lFDR plots • It has been suggested (Aubert, et al., 2004) that the first abrupt change of the local FDR can be an indication for the determination of a good threshold to choose genuinely statistically significant features.

  20. Step 7: Result interpretationlocal FDR 1st abrupt change of lFDR

  21. Step 7: Result interpretationlocal FDR Click to download result file

  22. Step 7: Result interpretationlocal FDR • Local FDR results: • 1st column: feature name • 2nd column: t or U test P value • 3rd column: local FDR results

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