Dramir36 Week 7 - Revision history

Dramir36: added STEM section of methods

2019-10-22T22:50:54Z

added STEM section of methods

Dramir36: /* Sanity Check: Number of genes significantly changed */ indent

2019-10-22T22:47:34Z

‎Sanity Check: Number of genes significantly changed: indent

Dramir36: /* Sanity Check: Number of genes significantly changed */ added answer to first question

2019-10-22T22:47:22Z

‎Sanity Check: Number of genes significantly changed: added answer to first question

Dramir36: added the rest of the methods from Week 7

2019-10-22T22:44:37Z

added the rest of the methods from Week 7

Dramir36: /* Data/Files */ renamed to Data file

2019-10-22T22:40:42Z

‎Data/Files: renamed to Data file

Dramir36: /* Data/Files */ inserted updated file

2019-10-22T22:40:04Z

‎Data/Files: inserted updated file

Dramir36: /* Notes/Methods/Results */ modified methods

2019-10-19T00:02:24Z

‎Notes/Methods/Results: modified methods

Show changes

Dramir36: /* Acknowledgments */ added week 8

2019-10-18T23:53:24Z

‎Acknowledgments: added week 8

Dramir36: /* Data/Files */ added updated excel file zip

2019-10-18T23:52:50Z

‎Data/Files: added updated excel file zip

Dramir36: /* Notes/Methods/Results */ added methods from week 8

2019-10-18T23:49:26Z

‎Notes/Methods/Results: added methods from week 8

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 * Comparing results with known data:  the expression of the gene ''NSR1'' (ID: YGR159C)is known to be induced by cold shock. '''''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?'''''  Note that the average Log fold change is what we called "STRAIN)_AvgLogFC_(TIME)" in step 3 of the ANOVA analysis. Does ''NSR1'' change expression due to cold shock in this experiment?
 * For fun, find "your favorite gene" (from your [[Week 3]] assignment) in the 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?'''''  Does your favorite gene change expression due to cold shock in this experiment?
 ==Data/Files==

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 * Click on the drop-down arrow for the unadjusted p value.  Set a criterion that will filter your data so that the p value has to be less than 0.05.
 ** '''''How many genes have p < 0.05?  and what is the percentage (out of 6189)?'''''
-:There are 2,479 genes that have p < 0.05, which is 40% of the total genes.
+::There are 2,479 genes that have p < 0.05, which is 40% of the total genes.
 ** '''''How many genes have p < 0.01? and what is the percentage (out of 6189)?'''''

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 Before we move on to further analysis of the data, we want to perform a more extensive sanity check to make sure that we performed our data analysis correctly.  We are going to find out the number of genes that are significantly changed at various p value cut-offs.
-* Go to your (STRAIN)_ANOVA worksheet.
+* Go to your dHAP4_ANOVA worksheet.
 * Select row 1 (the row with your column headers) and select the menu item Data > Filter > Autofilter (The funnel icon on the Data tab).  Little drop-down arrows should appear at the top of each column.  This will enable us to filter the data according to criteria we set.
 * Click on the drop-down arrow for the unadjusted p value.  Set a criterion that will filter your data so that the p value has to be less than 0.05.
 ** '''''How many genes have p < 0.05?  and what is the percentage (out of 6189)?'''''
 ** '''''How many genes have p < 0.01? and what is the percentage (out of 6189)?'''''
 ** '''''How many genes have p < 0.001? and what is the percentage (out of 6189)?'''''
 ** '''''How many genes have p < 0.0001? and what is the percentage (out of 6189)?'''''
 ** Note that it is a good idea to create a new worksheet in your workbook to record the answers to these questions.  Then you can write a formula in Excel to automatically calculate the percentage for you.
 * When we use a p value cut-off of p < 0.05, what we are saying is that you would have seen a gene expression change that deviates this far from zero by chance less than 5% of the time.

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 # Select columns A through G.  Now sort them by your MasterIndex in Column A in ascending order.
 # Copy column G and use Paste special > Paste values to paste it into the next column on the right of your ANOVA sheet.
 ==Data/Files==

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 ==Data/Files==
-*Startup File: [[File:BIOL367 F19 microarray-data dHAP4 DR.xlsx]]
+*Data File: [[File:BIOL367 F19 microarray-data dHAP4 DR.xlsx]]
 ==Conclusion==

← Older revision		Revision as of 22:40, 22 October 2019
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	*Startup File: [[File:BIOL367 F19 microarray-data dHAP4 DR.xlsx]]		*Startup File: [[File:BIOL367 F19 microarray-data dHAP4 DR.xlsx]]
−
−	*Excel file for October 22nd: [[File:10 18 2019 BIOL367 F19 microarray-data dHAP4 DR.zip]]

	==Conclusion==		==Conclusion==

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 ==Acknowledgments==
-*Copied purpose and methods/procedure from [[Week 7]] assignment page to individual journal and modified steps to relate to the dHAP4 data
+*Copied purpose and methods/procedure from [[Week 7]] and [[Week 8]] assignment page to individual journal and modified steps to relate to the dHAP4 data
 ==References==

← Older revision		Revision as of 23:52, 18 October 2019
Line 121:		Line 121:

	*Startup File: [[File:BIOL367 F19 microarray-data dHAP4 DR.xlsx]]		*Startup File: [[File:BIOL367 F19 microarray-data dHAP4 DR.xlsx]]
		+
		+	*Excel file for October 22nd: [[File:10 18 2019 BIOL367 F19 microarray-data dHAP4 DR.zip]]

	==Conclusion==		==Conclusion==

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 ** Each of the column headings from the data begin with the experiment name ("wt" for wild type ''S. cerevisiae'' data, "dCIN5" for the ''Δcin5'' data, etc.).  "LogFC" stands for "Log<sub>2</sub> Fold Change" which is the Log<sub>2</sub> red/green ratio.  The timepoints are designated as "t" followed by a number in minutes.  Replicates are numbered as "-0", "-1", "-2", etc. after the timepoint.
 *** The timepoints are t15, t30, t60 (cold shock at 13°C) and t90 and t120 (cold shock at 13°C followed by 30 or 60 minutes of recovery at 30°C).
 ==Data/Files==