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Differential Analysis & FDR Correction

Differential Analysis & FDR Correction . Correlation 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 correlation algorithm 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. Correlation 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 correlation algorithm 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: “sample” • 1st Column: patient names or IDs • 1st Row: . • Cell A2: clinical parameter • Cell A3 & others: gene name • 2nd column: values of one clinical parameter • All other cells should be molecular data, • one sample/patient per row • 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.cor.txt” selected

  9. Step 4: Choose algorithm for correlation analysis Choose correlation algorithm

  10. Step 4: which one to choose? • Rank based correlation – study relationship between different rankings on the same set of items • During the analysis, raw scores are converted to rankings • Spearman • Kendall • Pearson product-moment correlation coefficient

  11. To correlate a clinical variable to molecular data:Spearman’s rank, Kendall tau, or Pearson product-moment correlation coefficient analysis? Spearman’s Rank Correlation Coefficient Analysis: Spearman rank correlation is used when you have two measurement variables and one “hidden” nominal variable, which groups the measurements into pairs. It is a non-parametric test for correlation and used when one or both of the variables consists of ranks. Kendall Tau Correlation Coefficient Analysis: Kendall's Tau Correlation Coefficient analysis is a measure of correlation and measures the strength of the relationship between two variables. It provides a distribution free test of independence and a measure of the strength of dependence between two variables. It is required two variables, X and Y, that are paired observations. Both variables that are provided should be at least ordinal. Pearson Product-Moment Correlation Coefficient Analysis: The Pearson product-moment correlation coefficient is a common measure of the correlation (linear dependence) between two variables X and Y. It is very widely used in the sciences as a measure of the strength of linear dependence between two variables, giving a value somewhere between +1 and -1 inclusive.

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

  13. Step 6: Result interpretationGlobal FDR Single hypothesis test = correlation between one gene and one clinical variable

  14. 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

  15. Step 6: Result interpretationGlobal FDR

  16. 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

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

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

  19. Step 7: Result interpretationlocal FDR

  20. 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.

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

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

  23. Step 7: Result interpretationlocal FDR • Local FDR results: • 1st column: feature name • 2nd column: correlation test P value • 3rd column: local FDR results

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