Hivanson Week 9 - Revision history

Hivanson: /* Conclusion */ added data and percentages to conclusion

2024-03-21T06:50:30Z

‎Conclusion: added data and percentages to conclusion

Hivanson: /* References */ added reference

2024-03-21T06:46:50Z

‎References: added reference

Hivanson: /* References */ added reference

2024-03-21T06:41:46Z

‎References: added reference

Hivanson: /* Acknowledgments */ academic honesty statement

2024-03-21T06:40:50Z

‎Acknowledgments: academic honesty statement

Hivanson: /* Acknowledgments */

2024-03-21T06:40:08Z

‎Acknowledgments

Hivanson: /* Conclusion */ added a conclusion

2024-03-21T06:37:41Z

‎Conclusion: added a conclusion

Hivanson: /* Data & Files */ added "for dcin5"

2024-03-21T06:33:09Z

‎Data & Files: added "for dcin5"

Hivanson: /* Purpose */ purpose created

2024-03-21T06:32:17Z

‎Purpose: purpose created

Hivanson: /* Sanity Check: Number of genes significantly changed */ changed final question on both genes

2024-03-21T06:21:16Z

‎Sanity Check: Number of genes significantly changed: changed final question on both genes

Hivanson: /* Sanity Check: Number of genes significantly changed */ reformat questions about individual genes

2024-03-21T06:19:06Z

‎Sanity Check: Number of genes significantly changed: reformat questions about individual genes

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 ===Conclusion===
-The week 9 procedure walked us through how to run an ANOVA on Excel using DNA microarray data on the effects of cold stress on all genes in the ''S. cerevisiae'' genome. The results yielded were various types of p-values (standard, Bonferroni, and Benjamini & Hochberg) with different levels of stringency for cutoff. This exploration allowed us to better understand how p values are used in statistics, and how different modifications of the p value may be applied. This was the first time that I learned about the lower right corner double click trick to copy an equation to all cells in a column, which will be useful for biological database uses and beyond. Further, I learned how to filter data in an Excel sheet. Both of these skills are fairly basic, but I was never formally taught Excel and just didn't look into either function. Overall, I learned a lot about both Excel and statistics through this exercise.
+The week 9 procedure walked us through how to run an ANOVA on Excel using DNA microarray data on the effects of cold stress on all genes in the ''S. cerevisiae'' genome. The results yielded were various types of p-values (standard, Bonferroni, and Benjamini & Hochberg) with different levels of stringency for cutoff. Based on percentages of ∆CIN5 genes significant at the specified level, stringency was highest for standard p < 0.05 (37.0%), then Benjamini & Hochberg p < 0.05 (23.5%), standard p < 0.01 (22.3%), standard p < 0.001 (11.2%), standard p < 0.0001 (5.8%), and finally Bonferroni p < 0.05 (2.4%).
 ===Acknowledgments===

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 ===References===
 * LMU BioDB 2024. (2024). Week 9. Retrieved March 20, 2024, from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_9.
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← Older revision		Revision as of 06:41, 21 March 2024
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	===References===		===References===
		+	* LMU BioDB 2024. (2024). Week 9. Retrieved March 20, 2024, from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_9.

	{{Template:Hivanson}}		{{Template:Hivanson}}

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 ===Acknowledgments===
 I worked with my homework partner [[User:Nstojan1|Natalija Stojanovic]] in class on 3/13/2024 and 3/18/2024 under the guidance of [[User:Kdahlquist|Dr. Kam Dahlquist]]. All procedure was edited from [https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_9 LMU Bio DB Week 9].
 ===References===
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 ===Acknowledgments===
 ===References===
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← Older revision		Revision as of 06:37, 21 March 2024
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	===Conclusion===		===Conclusion===
		+	The week 9 procedure walked us through how to run an ANOVA on Excel using DNA microarray data on the effects of cold stress on all genes in the ''S. cerevisiae'' genome. The results yielded were various types of p-values (standard, Bonferroni, and Benjamini & Hochberg) with different levels of stringency for cutoff. This exploration allowed us to better understand how p values are used in statistics, and how different modifications of the p value may be applied. This was the first time that I learned about the lower right corner double click trick to copy an equation to all cells in a column, which will be useful for biological database uses and beyond. Further, I learned how to filter data in an Excel sheet. Both of these skills are fairly basic, but I was never formally taught Excel and just didn't look into either function. Overall, I learned a lot about both Excel and statistics through this exercise.

	===Acknowledgments===		===Acknowledgments===

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 ===Data & Files===
-[[Media:HI_BIOL367_S24_microarray-data_dCIN5.xlsx|Excel microarray data]]
+[[Media:HI_BIOL367_S24_microarray-data_dCIN5.xlsx|Excel microarray data for ∆CIN5]]
 [[Media:BIOL367_S24_hivanson_dCIN5_p-value_slide.pptx|p value table slide for ∆CIN5]]

← Older revision		Revision as of 06:32, 21 March 2024
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	===Purpose===		===Purpose===
		+	The purpose of this procedure is to run an ANOVA test on the up- or down-regulation of all yeast genes in the ''S. cerevisiae'' genome. We will view different variations of p-values to understand how certain cutoffs can be more or less stringent, and learn when each type should be used, as well as what level of significance is appropriate for different uses.

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

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 *Average Log fold change @ 90 minutes: -2.900925
 *Average Log fold change @ 120 minutes: -0.9315
-*NSR1 shows increased expression from time 15 minutes through 60 minutes. At 90 minutes, NSR1 expression decreases, and at 120 minutes, the expression of NSR1 remains decreased. There is a significant increase or decrease at at least one of these points.
+*NSR1 shows increased expression from time 15 minutes through 60 minutes. At 90 minutes, NSR1 expression decreases, and at 120 minutes, the expression of NSR1 remains decreased. There could be considered a significant increase or decrease for at least one of these points, as all p values are below 0.05. Further testing could be done to confirm which point/s this includes.
 '''What is IMD3's unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is IMD3's average Log fold change at each of the timepoints in the experiment?'''
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 *Average Log fold change @ 90 minutes: -0.608333333
 *Average Log fold change @ 120 minutes: -0.168133333
 ===Data & Files===

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 '''Find NSR1 in your dataset. What is its unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is its average Log fold change at each of the timepoints in the experiment?'''
+*Unadjusted p value: 6.37625E-08
-Unadjusted p value: 6.37625E-08
+*Bonferroni-corrected p value: 0.000394626
+*B-H-corrected p value: 2.19237E-05
-Bonferroni-corrected p value: 0.000394626
+*Average Log fold change @ 15 minutes: 4.070025
+*Average Log fold change @ 30 minutes: 3.611475
-B-H-corrected p value: 2.19237E-05
+*Average Log fold change @ 60 minutes: 4.2985
+*Average Log fold change @ 90 minutes: -2.900925
-average Log fold change @ 15 minutes: 4.070025
+*Average Log fold change @ 120 minutes: -0.9315
+*NSR1 shows increased expression from time 15 minutes through 60 minutes. At 90 minutes, NSR1 expression decreases, and at 120 minutes, the expression of NSR1 remains decreased. There is a significant increase or decrease at at least one of these points.
 '''What is IMD3's unadjusted, Bonferroni-corrected, and B-H-corrected p values? What is IMD3's average Log fold change at each of the timepoints in the experiment?'''
+*Unadjusted p value: 0.111670609
-Unadjusted p value: 0.111670609
+*Bonferroni-corrected p value: 1
+*B-H-corrected p value: 0.232000469
-Bonferroni-corrected p value: 1
+*Average Log fold change @ 15 minutes: 1.638433333
+*Average Log fold change @ 30 minutes: -0.100766667
-B-H-corrected p value: 0.232000469
+*Average Log fold change @ 60 minutes: 1.659233333
+*Average Log fold change @ 90 minutes: -0.608333333
-average Log fold change @ 15 minutes: 1.638433333
+*Average Log fold change @ 120 minutes: -0.168133333
 ===Data & Files===