Lenaolufson Week 15

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12/8/15

  • It was now time for me to prepare my file for GenMAPP, and I did so by the Vibrio cholerae instructions found here.]
  • I inserted a new worksheet and named it "forGenMAPP".
  • I went back to the "statistics" worksheet and Selected All and Copied.
  • I went to my new sheet and clicked on cell A1 and selected Paste Special, clicked on the Values radio button, and clicked OK.
    • I then deleted the ID columns besides the far left one in column A, and I deleted the second MasterIndex column because it was unnecessary.
    • I added a "1" before all of the titles of columns D through I so that none of the columns would have the same names due to the replicates.
  • I selected Columns V through Y (all the fold changes). I selected the menu item Format > Cells. Under the number tab, I selected 2 decimal places. I clicked OK.
  • I selected all the columns containing p values. I selected the menu item Format > Cells. Under the number tab, I selected 4 decimal places. I clicked OK.
  • I deleted the left-most Bonferroni p value column, preserving the one that showed the result of my "if" statement.
  • I inserted a column to the right of the "ID" column. I typed the header "SystemCode" into the top cell of this column. I filled the entire column (each cell) with the letter "N".
  • I selected the menu item File > Save As, and chose "Text (Tab-delimited) (*.txt)" from the file type drop-down menu.
  • After preparing it for GenMAPP, here are the .xls and .txt files:
  • Then it was time to perform a sanity check, which was done using the Vibrio cholerae instructions found here.]
  • I opened my spreadsheet and went to the "forGenMAPP" tab.
  • I clicked on cell A1 and selected the menu item Data > Filter > Autofilter. Little drop-down arrows appeared at the top of each column. This enabled me to filter the data according to criteria I set.
  • I clicked on the drop-down arrow on my "Pvalue" column. I selected "Custom". In the window that appeared, I set a criterion that filtered my data so that the Pvalue was less than 0.05.
    • p-value less than 0.05: 1923/3552, 54%
    • p-value less than 0.01: 1028/3552, 29%
    • p-value less than 0.001: 242/3552, 7%
    • p-value less than 0.0001: 40/3552, 1%
    • p < 0.05 for the Bonferroni-corrected p value: 9/3552, 0.2%
    • p < 0.05 for the Benjamini and Hochberg-corrected p value: 1365/3552, 38%
  • Keeping the (unadjusted) "Pvalue" filter at p < 0.05, I filtered the "Avg_ABC_Samples" column to show all genes with an average log fold change greater than zero.
    • 964/3552, 27%
  • Keeping the (unadjusted) "Pvalue" filter at p < 0.05, I filtered the "Avg_ABC_Samples" column to show all genes with an average log fold change less than zero.
    • 959/3552, 27%
  • With an average log fold change of > 0.25 and p < 0.05
    • 874/3552, 25%
  • With an average log fold change of < -0.25 and p < 0.05
    • 848/3552, 24%
  • the fold change cut-off of greater than 0.25 or less than -0.25 and the unadjusted p value cut off of p < 0.05
    • 1722/3552, 48%
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