Cdomin12 Week 8
Contents
Purpose
Methods/Results
Statistical Analysis Part 1: ANOVA
- Created a new worksheet, naming it "wt_ANOVA"
- Copied the first three columns containing the "MasterIndex", "ID", and "Standard Name" from the "Master_Sheet" worksheet and pasted it into new worksheet. Copied the columns containing the data for your strain and pasted it into your new worksheet.
- At the top of the first column to the right of your data, created five column headers of the form wt_AvgLogFC_(TIME) where STRAIN is your strain designation and (TIME) is 15, 30, etc.
- In the cell below the wt_AvgLogFC_t15 header, typed
=AVERAGE(
- Then highlighted all the data in row 2 associated with t15, pressed the closing paren key (shift 0),and pressed the "enter" key.
- This cell now contains the average of the log fold change data from the first gene at t=15 minutes.
- Clicked on this cell and position your cursor at the bottom right corner. You should see your cursor change to a thin black plus sign (not a chubby white one). When it does, double clicked, and the formula was copied to the entire column of 6188 other genes.
- Repeated steps (4) through (8) with the t30, t60, t90, and the t120 data.
- Now in the first empty column to the right of the wt_AvgLogFC_t120 calculation, createde the column header wt_ss_HO.
- In the first cell below this header, type
=SUMSQ(
- Highlighted all the LogFC data in row 2 (but not the AvgLogFC), pressed the closing paren key (shift 0),and pressed the "enter" key.
- In the next empty column to the right of wt_ss_HO, created the column headers wt_ss_(TIME) as in (3).
- Made a note of how many data points you have at each time point for your strain. For most of the strains, it will be 4, but for dHAP4 t90 or t120, it will be "3", and for the wild type it will be "4" or "5". Counted carefully. Also, made a note of the total number of data points. Again, for most strains, this will be 20, but for example, dHAP4, this number will be 18, and for wt it should be 23 (double-check).
- In the first cell below the header wt_ss_t15, type
=SUMSQ(D2:G2)-COUNTA(D2:G2)*AA2^2
and hit enter.- The
COUNTA
function counts the number of cells in the specified range that have data in them (i.e., does not count cells with missing values). - The phrase <range of cells for logFC_t15> was replaced by the data range associated with t15.
- The phrase <AvgLogFC_t15> was replaced by the cell number in which computed the AvgLogFC for t15, and the "^2" squares that value.
- Upon completion of this single computation, used the Step (7) trick to copy the formula throughout the column.
- The
- Repeated this computation for the t30 through t120 data points. Again, be sure to get the data for each time point, type the right number of data points, and get the average from the appropriate cell for each time point, and copy the formula to the whole column for each computation.
- In the first column to the right of wt_ss_t120, created the column header wt_SS_full.
- In the first row below this header, type
=sum=AL2
and hit enter. - In the next two columns to the right, created the headers wt_Fstat and wt_p-value.
- Recall the number of data points from (13): call that total n.
- In the first cell of the (STRAIN)_Fstat column, type
=((23-5)/5)*(((AF2)-(AL2))/(AL2))code> and hit enter.
- Don't actually type the n but instead use the number from (13). Also note that "5" is the number of timepoints.
- Replaced the phrase wt_ss_HO with the cell designation.
- Replaced the phrase <wt_SS_full> with the cell designation.
- Copied to the whole column.
- In the first cell below the wt_p-value header, type
=FDIST(AM2,5,23-5)
replacing the phrase <(STRAIN)_Fstat> with the cell designation and the "n" as in (13) with the number of data points total. . Copied to the whole column.- Clicked on cell A1 and click on the Data tab. Selected the Filter icon (looks like a funnel). Little drop-down arrows appeared at the top of each column. This enabled us to filter the data according to criteria we set.
- Clicked on the drop-down arrow on your wt_p-value column. Selected "Number Filters". In the window that appears, set a criterion that filtered data so that the p value has to be less than 0.05.
- Excel will now only display the rows that correspond to data meeting that filtering criterion. A number appeared in the lower left hand corner of the window the number of rows that meet that criterion.
- Undid any filters applied before making any additional calculations.
2,528/6189 records found to have P<0.05
NSR1
unadjusted:2.86939E-10
Bonferroni-corrected:1.77586E-06
B-H-corrected: 8.87932E-07
average log fold change 15m:3.279225
average log fold change 30m:3.621
average log fold change 60 m:3.526525
average log fold change 90m:-2.04985
average log fold change 120m:-0.60622
Favorite Gene: YPL153C
unadjusted: 0.005415
Bonferroni-corrected: 33.50424111
B-H-corrected: 0.023931601
average log fold change 15m: -0.57335
average log fold change 30m: -0.78184
average log fold change 60 m: -0.7237
average log fold change 90m: 0.7496
average log fold change 120m: -0.25624
Data and Files
Conclusion
Acknowledgments
1. I worked with User:Knguye66, User:Jcowan4, and User:Mavila9 for this assignment.
2."Except for what is noted above, this individual journal entry was completed by me and not copied from another source."
References
- Week 8. Retrieved October 15, 2019, from https://xmlpipedb.cs.lmu.edu/biodb/fall2019/index.php/Week_8