Cdomin12 Week 8 - Revision history

Cdomin12: spelling check

2019-10-23T20:04:26Z

spelling check

Cdomin12: /* Favorite Gene: YPL153C */ added space

2019-10-23T05:23:17Z

‎Favorite Gene: YPL153C: added space

Cdomin12: /* NSR1 */ added space

2019-10-23T05:23:08Z

‎NSR1: added space

Cdomin12: /* Conclusion */ added

2019-10-23T05:14:02Z

‎Conclusion: added

Cdomin12: /* Purpose */ added

2019-10-23T05:09:28Z

‎Purpose: added

Cdomin12: /* Sanity Check: Number of genes significantly changed */ changed slide

2019-10-23T05:05:52Z

‎Sanity Check: Number of genes significantly changed: changed slide

Cdomin12: /* Data and Files */ deleted extra file

2019-10-23T05:00:05Z

‎Data and Files: deleted extra file

Cdomin12: /* Data and Files */ edited files

2019-10-23T04:59:45Z

‎Data and Files: edited files

Cdomin12: /* Sanity Check: Number of genes significantly changed */ deleted bullet

2019-10-23T04:56:32Z

‎Sanity Check: Number of genes significantly changed: deleted bullet

Cdomin12: /* Statistical Analysis Part 1: ANOVA */ changed code from =sum

2019-10-23T04:55:46Z

‎Statistical Analysis Part 1: ANOVA: changed code from =sum

@@ Line 8: / Line 8: @@
 ==== 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.
+# 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 wt and pasted it into 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.
+# 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 wt and (TIME) is 15, 30, etc.
 # In the cell below the wt_AvgLogFC_t15 header, typed <code>=AVERAGE</code>
 # 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.
+# This cell now contained 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.
+# Clicked on this cell and positioned cursor at the bottom right corner. Double clicked black cross, 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.
+# Now in the first empty column to the right of the wt_AvgLogFC_t120 calculation, created the column header wt_ss_HO.
-# In the first cell below this header, type <code>=SUMSQ(</code>
+# In the first cell below this header, typed <code>=SUMSQ(</code>
 # 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).
+# Made a note of how many data points 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 <code>=SUMSQ(D2:G2)-COUNTA(D2:G2)*AA2^2</code> and hit enter.
 #* The <code>COUNTA</code> function counts the number of cells in the specified range that have data in them (i.e., does not count cells with missing values).
@@ Line 25: / Line 25: @@
 #* 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.
-# 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.
+# Repeated this computation for the t30 through t120 data points.  Again, be sure to get the data for each time point, typed the right number of data points, and got the average from the appropriate cell for each time point, and copied 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 <code>=SUM(AG2:AK2)</code> and hit enter.
@@ Line 36: / Line 36: @@
 #* 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 <code>=FDIST(AM2,5,23-5)</code> replacing the phrase <(STRAIN)_Fstat> with the cell designation and the "n" as in (13) with the number of data points total. <!--(Again, note that the number of timepoints is actually "4" for the dSWI4 strain)-->.  Copied to the whole column.
+# In the first cell below the wt_p-value header, type <code>=FDIST(AM2,5,23-5)</code> replaced the phrase <(STRAIN)_Fstat> with the cell designation and the "n" as in (13) with the number of data points total. <!--(Again, note that the number of timepoints is actually "4" for the dSWI4 strain)-->.  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 cell A1 and clicked 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.
@@ Line 59: / Line 59: @@
 # Typed the header "Rank" in cell E1.  Created a series of numbers in ascending order from 1 to 6189 in this column.  This is the p value rank, smallest to largest.  Typed "1" into cell E2 and "2" into cell E3. Selected both cells E2 and E3. Double-clicked on the plus sign on the lower right-hand corner of your selection to fill the column with a series of numbers from 1 to 6189.
 # Calculated the Benjamini and Hochberg p value correction. Type wt_B-H_p-value in cell F1. Typed the following formula in cell F2: <code>=(D2*6189)/E2</code> and press enter. Copy that equation to the entire column.
-# Type "STRAIN_B-H_p-value" into cell G1.
+# Typed "STRAIN_B-H_p-value" into cell G1.
-# Type the following formula into cell G2: <code>=IF(F2>1,1,F2)</code> and press enter. Coped that equation to the entire column.
+# Typed the following formula into cell G2: <code>=IF(F2>1,1,F2)</code> and pressed enter. Copied that equation to the entire column.
 # Selected columns A through G.  Sorted them by MasterIndex in Column A in ascending order.
 # Copied column G and used Paste special > Paste values and pasted it into the next column on the right of your ANOVA sheet.

← Older revision		Revision as of 05:23, 23 October 2019
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	Does your favorite gene change expression due to cold shock in this experiment?		Does your favorite gene change expression due to cold shock in this experiment?
		+
	My favorite gene barely changes expression during cold shock. It stays close in negative values indicating that gene expression is not changing by much.		My favorite gene barely changes expression during cold shock. It stays close in negative values indicating that gene expression is not changing by much.

@@ Line 102: / Line 102: @@
 Does ''NSR1'' change expression due to cold shock in this experiment?
 Yes, expression changes and it starts to show negative values indicating that expression of genes are less expressed during cold shock.
 * Found "your favorite gene" (from your [[Week 3]] assignment) in the dataset:
 ===Favorite Gene: YPL153C===

← Older revision		Revision as of 05:14, 23 October 2019
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	==Conclusion==		==Conclusion==
		+	Using the excel program, we were able to conduct p value correction by using ANOVA to calculate a Bonferroni p value and B-H p value. These are important skills in learning how to properly calculate and evaluate p values. With a big emphasis on p values in statistical analysis in research, it is important to more closely examine how these values are obtained and how to interpret them. The beginning of using the STEM program is also important in learning how to properly conduct data conversion and interoperability in order to use your data in multiple different programs and in multiple different formats.

	==Acknowledgments==		==Acknowledgments==

← Older revision		Revision as of 05:09, 23 October 2019
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	==Purpose==		==Purpose==
		+	To conduct statistical analysis using p values in order to further analyze and correct data while practicing and utilizing Excel skills and knowledge. Also, to begin using STEM software to practice the core competency of "Data Conversion and Interoperability".

	==Methods/Results==		==Methods/Results==

← Older revision		Revision as of 05:05, 23 October 2019
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	** '''''How many genes are p < 0.05 for the Benjamini and Hochberg-corrected p value? and what is the percentage (out of 6189)?'''''		** '''''How many genes are p < 0.05 for the Benjamini and Hochberg-corrected p value? and what is the percentage (out of 6189)?'''''

−	Answer to above question are located at the following link: [[Media:P-value ~~slideCD~~.pptx \|p value slide]]	+	Answer to above question are located at the following link: [[Media:P-value slideCD2.pptx \|p value slide]]

← Older revision		Revision as of 05:00, 23 October 2019
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	[[Media:BIOL367 F19 microarray-data wt (2)CDupdate1.txt \| text file for STEM analysis]]		[[Media:BIOL367 F19 microarray-data wt (2)CDupdate1.txt \| text file for STEM analysis]]
−
−	~~[[Media:BIOL367 F19 microarray-data wt (2)CDupdate1.xlsx \| excel file]]~~

	==Conclusion==		==Conclusion==

@@ Line 157: / Line 157: @@
 ==Data and Files==
-[[File:BIOL367 F19 microarray-data wt (1)CDupdate1.zip]]
+[[Media:BIOL367 F19 microarray-data wt (2)CDupdate1.xlsx.zip | Zip File for Interim Deadline]]
-[[Media:BIOL367 F19 microarray-data wt (1)CDupdate1.zip | Interim File]]
+[[Media:BIOL367 F19 microarray-data wt (2)CDupdate1.txt | text file for STEM analysis]]
 [[Media:BIOL367 F19 microarray-data wt (2)CDupdate1.xlsx | excel file]]

@@ Line 80: / Line 80: @@
 Answer to above question are located at the following link: [[Media:P-value slideCD.pptx |p value slide]]
-* Compared results with known data:
 ===NSR1===
 unadjusted:2.86939E-10

@@ Line 26: / Line 26: @@
 # 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 <code>=sum=AL2</code> and hit enter.
+# In the first row below this header, type <code>=SUM(AG2:AK2)</code> 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.