Sulfiknights DA Week 12/13 - Revision history

Mavila9: /* Acknowledgments */ fix dataset

2019-11-26T07:50:25Z

‎Acknowledgments: fix dataset

2019-11-26T07:49:52Z

‎Acknowledgments: added

2019-11-26T07:35:29Z

‎Conclusion: add to conclusion

2019-11-26T07:32:13Z

‎Purpose: adding purpose

2019-11-26T02:56:28Z

‎Data & Files: edited

2019-11-26T02:56:19Z

‎Data & Files: added ppt

2019-11-26T02:56:00Z

‎Sanity Check: added steps

2019-11-26T02:46:51Z

‎Methods & Results: added header

2019-11-26T02:21:38Z

‎Conclusion: added conclusion

2019-11-26T02:17:47Z

‎Methods & Results: added steps

@@ Line 54: / Line 54: @@
 ==Acknowledgments==
-We would like to thank Dr. Dahlquist for providing the instructions in [[Week 8]] that were referenced to perform the ANOVA of the datasetA and for reviewing the analysis. We would also like to thank Thorsen et al. for providing the datasets.
+We would like to thank Dr. Dahlquist for providing the instructions in [[Week 8]] that were referenced to perform the ANOVA of the SetA family dataset and for reviewing the analysis. We would also like to thank Thorsen et al. for providing the datasets.
 ==References==
 *LMU BioDB 2019. (2019). Week 8. Retrieved November 25, 2019, from [https://xmlpipedb.cs.lmu.edu/biodb/fall2019/index.php/Week_8 https://xmlpipedb.cs.lmu.edu/biodb/fall2019/index.php/Week_8].
 *Thorsen, M., Lagniel, G., Kristiansson, E., Junot, C., Nerman, O., Labarre, J., & Tamás, M. J. (2007). Quantitative transcriptome, proteome, and sulfur metabolite profiling of the Saccharomyces cerevisiae response to arsenite. Physiological genomics, 30(1), 35-43. DOI: https://doi.org/10.1152/physiolgenomics.00236.2006

@@ Line 54: / Line 54: @@
 ==Acknowledgments==
 ==References==
 *LMU BioDB 2019. (2019). Week 8. Retrieved November 25, 2019, from [https://xmlpipedb.cs.lmu.edu/biodb/fall2019/index.php/Week_8 https://xmlpipedb.cs.lmu.edu/biodb/fall2019/index.php/Week_8].
 *Thorsen, M., Lagniel, G., Kristiansson, E., Junot, C., Nerman, O., Labarre, J., & Tamás, M. J. (2007). Quantitative transcriptome, proteome, and sulfur metabolite profiling of the Saccharomyces cerevisiae response to arsenite. Physiological genomics, 30(1), 35-43. DOI: https://doi.org/10.1152/physiolgenomics.00236.2006

@@ Line 51: / Line 51: @@
 ==Conclusion==
-We were able to reorganize the data in the way that was best suited for further ANOVA, statistical, and database analyses. We determined that a certain number of genes have p-values less than 0.05, and BH values were determined as well. So far, ANOVA analysis has been completed on the SetA family dataset.
+We were able to reorganize the data in the way that was best suited for further ANOVA, statistical, and database analyses. We determined that a certain number of genes have p-values less than 0.05, and BH values were determined as well. So far, ANOVA analysis has only been completed on the SetA family dataset because the other datasets include varying conditions. The statistical significance found is in line with the results of Thorsen et al. that observed an increase in genes associated with sulfate assimilation and glutathione biosynthesis pathways.
 ==Acknowledgments==

@@ Line 1: / Line 1: @@
 {{Sulfiknights}}
 ==Purpose==
 ==Methods & Results==

@@ Line 46: / Line 46: @@
 ==Data & Files==
 [[Media:Thorsendata_sulfiknights.xlsx|Thorsen Data]]
 [[Media:Thorsendata_sulfiknights_pvalueslide.pptx|Thorsen P-value Slide]]

← Older revision		Revision as of 02:56, 26 November 2019
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	===Sanity Check===		===Sanity Check===
		+	#Selected row 1
		+	#Autofilter all headers
		+	#Filtered for how many p-values are <0.05 for unadjusted p-values, BH p-values, and Bonferroni p-values
		+	#Filtered for how many unadjusted p-values for <0.01, <0.001, and 0.0001
		+	*All values are reflected in [[Media:Thorsendata_sulfiknights_pvalueslide.pptx\|Thorsen P-value Slide]]

	==Data & Files==		==Data & Files==

@@ Line 36: / Line 36: @@
 #Genes were ranked by p-value and then by MasterIndex.
 #Column "swtVnwt_B-H_p-value" was created containing the equation =(D2*4785)/E2 and then replicated into column G. This column was then pasted into the previous sheet.
 ==Data & Files==

← Older revision		Revision as of 02:21, 26 November 2019
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	==Conclusion==		==Conclusion==
		+	We were able to reorganize the data in the way that was best suited for further ANOVA, statistical, and database analyses. We determined that a certain number of genes have p-values less than 0.05, and BH values were determined as well. So far, ANOVA analysis has been completed on the SetA family dataset.

	==Acknowledgments==		==Acknowledgments==

@@ Line 24: / Line 24: @@
 *ANOVA procedure was based on the methods from [[Week 8]].
 #A new sheet called "swtVnwt_1mM_ANOVA" was created and all data from Columns A-R was copied and pasted into this sheet.
-#Columns "swtVnwt_AvgLogFC_1mM_15m" - "swtVnwt_AvgLogFC_1mM_1080m" for each time point 15m, 30m, 60m, and 1080m were created and contain the equation the average of each replicate for each time point.
+#Columns S-V were called "swtVnwt_AvgLogFC_1mM_15m" changing the last part for each time point 15m, 30m, 60m, and 1080m respectively and contained the equation the average of each replicate for each time point.
-#Column "swtVnwt_ss_HO" was created containing the equation SUMSQ(D2:R2).
+#Column "swtVnwt_ss_HO" was created containing the equation SUMSQ(all LogFC values in row).
-#Sanity Check: 1068/4785 p-values are less than 0.05
+#Columns X-AA were named "swtVnwt_ss_15m" changing the last part for each time point 15m, 30m, 60m, and 1080m respectively and contained the equation =SUMSQ(average LogFC at that time point)-COUNTA(average LogFC at that time point)*V2^2.
 ==Data & Files==