Dbashour Week 8 - Revision history

Dbashour: added deliverable

2017-12-09T22:52:38Z

added deliverable

Dbashour: added summary

2017-12-09T22:48:35Z

added summary

Show changes

Dbashour: edited tense

2017-11-30T23:27:56Z

edited tense

Dbashour: /* Uploaded Powerpoint File */ syntax fix

2017-10-24T06:36:06Z

‎Uploaded Powerpoint File: syntax fix

Dbashour: powerpoint added

2017-10-24T06:35:31Z

powerpoint added

Dbashour: added references and template

2017-10-24T06:31:01Z

added references and template

Dbashour: added acknowledgements and signature

2017-10-24T06:29:43Z

added acknowledgements and signature

Dbashour: added summary and electronic notebook

2017-10-24T06:28:16Z

added summary and electronic notebook

Dbashour: /* ADH1 */ updated p value

2017-10-24T05:31:15Z

‎ADH1: updated p value

Dbashour: added adh1 information

2017-10-24T05:10:24Z

added adh1 information

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 ===Summary===
 Our strain was dGLN3 and we analyzed the data for timepoints 15, 30, 60, 90, and 120. We used that information to calculate the p-value of an ANOVA, the Bonferroni corrected p-value, and the Benjamini and Hochber corrected p-value for each timepoint. We learned how to use excel to facilitate with large datasets like this one. We learned shortcuts to highlighting information like double clicking in the corner of the box as well as dragging the box down to multiple cells in order to copy the function to those respective cells. We concluded by answering the questions related to our findings as well as analyzing the information from the "our favorite gene" assignment. In summary, we hoped to find genes that showed significantly different rates of gene expression from the start of the experiment (time 0) to the end, 120 minutes later. We determined this by performing an ANOVA and determining the significance of the results. We were able to determine what the effects of cold related osmotic shock was on gene expression. Specifically, we found that 1185 genes or 19.15% of the data in relation to the wildtype strain had a Benjamini & Hochberg-corrected p value of less than 0.05 and 45 genes or 0.73% of the data in relation to the wildtype strain had a Bonferroni-corrected p value of less than 0.05. Lastly, NSR1 has small p values indicating that it is significant and affected by the cold shock. ADH1, or our favorite gene, was most likely not affected by cold shock because of the p values being above 0.05, meaning that the average log fold changes we see are likely just noise.
 ==Acknowledgements==

@@ Line 5: / Line 5: @@
 The purpose of the witin-stain ANOVA test is to determine if any genes had a gene expression change that was significantly different than zero at '''''any''''' timepoint.
-# Create a new worksheet, naming it either "dGLN3_ANOVA" as appropriate.
+# Created a new worksheet, named it "dGLN3_ANOVA".
-# Copy the first three columns containing the "MasterIndex", "ID", and "Standard Name" from the "Master_Sheet" worksheet for your strain and paste it into your new worksheet.  Copy the columns containing the data for your strain and paste it into your new worksheet.
+# I copied the first three columns containing the "MasterIndex", "ID", and "Standard Name" from the "Master_Sheet" worksheet for my strain and pasted it into dGLN3_ANOVA. I copied the columns containing the data for dGLN3 and pasted it into dGLN3_ANOVA.
-# At the top of the first column to the right of your data, create five column headers of the form dGLN3_AvgLogFC_(TIME) where (TIME) is 15, 30, etc.
+# At the top of the first column to the right of your data, I created five column headers of the form dGLN3_AvgLogFC_(TIME) where (TIME) is 15, 30, etc.
-# In the cell below the dGLN3_AvgLogFC_t15 header, type <code>=AVERAGE(</code>
+# In the cell below the dGLN3_AvgLogFC_t15 header, I typed <code>=AVERAGE(</code>
-# Then highlight all the data in row 2 associated with dGLN3 and t15, press the closing paren key (shift 0),and press the "enter" key.
+# Then I highlighted all the data in row 2 associated with dGLN3 and t15 and 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.
-# Click 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 click, and the formula will magically be copied to the entire column of 6188 other genes.
+# I Clicked on this cell and positioned my 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 click, and the formula will magically be copied to the entire column of 6188 other genes.
 # Repeat steps (4) through (8) with the t30, t60, t90, and the t120 data.
 # Now in the first empty column to the right of the dGLN3_AvgLogFC_t120 calculation, create the column header dGLN3)_ss_HO.
 # In the first cell below this header, type <code>=SUMSQ(</code>

@@ Line 91: / Line 91: @@
 == Uploaded Powerpoint File ==
-[[Media: DGLN3_ppt_Dina.pptx | dGLN3 powerpoint
+[[Media: DGLN3_ppt_Dina.pptx | dGLN3 powerpoint]]
 ==P-Value Computations==

← Older revision		Revision as of 06:35, 24 October 2017
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	[[Media: DGLN3_ANOVA.zip \| dGLN3 zip file]]		[[Media: DGLN3_ANOVA.zip \| dGLN3 zip file]]
		+
		+	== Uploaded Powerpoint File ==
		+
		+	[[Media: DGLN3_ppt_Dina.pptx \| dGLN3 powerpoint

	==P-Value Computations==		==P-Value Computations==

← Older revision		Revision as of 06:31, 24 October 2017
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	[[User:Dbashour\|Dbashour]] ([[User talk:Dbashour\|talk]]) 23:29, 23 October 2017 (PDT)		[[User:Dbashour\|Dbashour]] ([[User talk:Dbashour\|talk]]) 23:29, 23 October 2017 (PDT)
		+
		+	==References==
		+	LMU BioDB 2017. (2017). Week 8. Retrieved October 23, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_8
		+
		+
		+	{{Template:dbashour}}

← Older revision		Revision as of 06:29, 24 October 2017
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	==Acknowledgements==		==Acknowledgements==
−	I worked with	+	I worked with [[user:Zvanysse \| Zack]] to complete this week's assignment. We worked in class in order to ask questions as we worked but completed the rest of the assignment separately over the weekend. We consulted via text if we had any questions regarding the assignment. While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.
		+
		+	[[User:Dbashour\|Dbashour]] ([[User talk:Dbashour\|talk]]) 23:29, 23 October 2017 (PDT)

← Older revision		Revision as of 06:28, 24 October 2017
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	#* @ 120 = 0.514075012		#* @ 120 = 0.514075012
	#As shown above, we can infer that gene expression started low but rose around the 60 interval then decreased a significant amount at the 90 interval, only to rise again at the last interval. This shows that cold shock affects the gene expression around the 30-60 interval and the 90-120 interval.		#As shown above, we can infer that gene expression started low but rose around the 60 interval then decreased a significant amount at the 90 interval, only to rise again at the last interval. This shows that cold shock affects the gene expression around the 30-60 interval and the 90-120 interval.
		+
		+	==Summary==
		+	In summary, we hoped to find genes that showed significantly different rates of gene expression from the start of the experiment (time 0) to the end, 120 minutes later. We determined this by performing an ANOVA and determining the significance of the results. We were able to determine what the effects of cold related osmotic shock was on gene expression.
		+
		+	==Electronic Notebook==
		+	We began this assignment by working in class on the [[Week 8]] homework. [[user:Zvanysse \| Zack]] and I worked in class to complete the excel worksheet by following the direct instructions on the assignment page. Our strain was dGLN3 and we analyzed the data for timepoints 15, 30, 60, 90, and 120. We used that information to calculate the p-value of an ANOVA, the Bonferroni corrected p-value, and the Benjamini and Hochber corrected p-value for each timepoint. We learned how to use excel to facilitate with large datasets like this one. We learned shortcuts to highlighting information like double clicking in the corner of the box as well as dragging the box down to multiple cells in order to copy the function to those respective cells. We concluded by answering the questions related to our findings as well as analyzing the information from the "our favorite gene" assignment.
		+
		+	==Acknowledgements==
		+	I worked with

@@ Line 113: / Line 113: @@
 ==ADH1==
 #Unaltered p-value = 0.772
-#Bonferonni-corrected P-Value: NA
+#Bonferonni-corrected P-Value: 4780.319
-#B-H-corrected P-Value: NA
+#B-H-corrected P-Value: 0.8617
 #Average Log Fold
 #* @ 15 = -0.902324179

@@ Line 104: / Line 104: @@
 #B-H corrected p-value = 0.008167
 #Average Log Fold:
-#*3.50622
+#* @ 15 = 3.50622
-#*4.53189
+#* @ 30 = 4.53189
-#*2.75921
+#* @ 60 = 2.75921
-#*-1.85027
+#* @ 90 = -1.85027
-#*-1.86741
+#* @ 120 = -1.86741
-#As shown above, we can infer that gene expression started off high but eventually decreased to a consistent level.
+#As shown above, we can infer that gene expression started off high but eventually decreased to a consistent level due to cold shock.