Dahlquist:Notebook/Microarray Data Analysis/2008/10/02

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Kevin's Edge Analysis from 10/2/2008

  • Login with your Keck lab username to mason (the names of the machines are on the lower-left corner of the login screens).
  • Right-click on the green tabula rasa.
  • Choose Terminal.
  • Type:
cd Desktop/edge_1.1.290
  • At this point, the R prompt shows up. Type:
  • The Edge GUI should now appear.
  • Create two tab-delimited text files for "genes" and "covariates".
    • Files in Desktop "Data analysis 2008-10-02"
    • Used gene file "wt-dCIN5_consolidated_Edge_genes-indexonly_20080715.txt"
    • Used covariate file "wt-dCIN5_consolidated_Edge_covariates_20080710.txt
  • Load both into an Edge session.
  • Select "Impute Missing Data" from the menu. Calculate Percent Missing Data by clicking on the button. The results are:
    • Percent of genes missing data: 7.63%
    • Percent of arrays missing data: 95.35%
    • Overall percent of missing data: 3.15%
  • For KNN Parameters, set:
    • Percent of missing values to tolerate in a gene: 100 (so all genes included)
    • Number of nearest neighbors to use (maximum of 15): 15
    • clicked GO to impute missing data.
  • Selected "Identify Differentially Expressed Genes"
    • Note: this is to compare between the wt and dCIN5 strains. Different parameters and gene/covariate files will need to be used to analyze individual strains.
    • Class Variable is: Strain
    • Differential Expression Type is: Time Course
    • Number of null iterations, set to 1000
    • Choose a seed for reproducible results, set to 47
    • Choose Time Course Settings
    • Covariate giving time points is: Timepoint
    • Covariate corresponding to individuals is: Flask
    • Choose spline type, accepted default of Natural Cubic Spline, dimension 4
    • Click "Apply" and then click "Go"
    • 1000 permutations looks like it will take about 10 minutes.
  • Save results as:
    • Choose Q-Value cutoff as 1, recalculate
    • Saved total list of genes as: "20081002_wt_dCIN5_comparison_results_genelist" in "Data analysis 2008-10-02"
    • Can cluster significant genes, did not do