Ebachour: Done with Week 10

2017-11-07T07:50:48Z

Done with Week 10

Ebachour: Added Template for page

2017-11-07T07:35:50Z

Added Template for page

New page

=Folder with PowerPoint and all files=
[[media:Ebachoura-week10.zip|Folder of Goodies]]
=Acknowledgements=
I worked with my homework partner [[User:Qlanners | Quinn Lanners]] in class. We also met face-to-face one time outside of class. We texted outside of class and met to work on the API part of the assignment together.<br>
'''While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.'''<br>
[[User:Ebachour|Ebachour]] ([[User talk:Ebachour|talk]]) 23:35, 6 November 2017 (PST)

=References=
* LMU BioDB 2017. (2017). Week 10. Retrieved November 6, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10

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← Older revision		Revision as of 07:50, 7 November 2017
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		+	=Electronic Journal=
		+	==== Clustering and GO Term Enrichment with stem ====
		+
		+	# '''Prepare your microarray data file for loading into STEM.'''
		+	#* Download your Excel workbook that you used for your [[Week 8]] assignment.
		+	#* Insert a new worksheet into your Excel workbook, and name it "(STRAIN)_stem".
		+	#* Select all of the data from your "(STRAIN)_ANOVA" worksheet and Paste special > paste values into your "(STRAIN)_stem" worksheet.
		+	#** Your leftmost column should have the column header "Master_Index". Rename this column to "SPOT". Column B should be named "ID". Rename this column to "Gene Symbol". Delete the column named "Standard_Name".
		+	#** Filter the data on the B-H corrected p value to be > 0.05 (that's '''greater than''' in this case).
		+	#*** Once the data has been filtered, select all of the rows (except for your header row) and delete the rows by right-clicking and choosing "Delete Row" from the context menu. Undo the filter. This ensures that we will cluster only the genes with a "significant" change in expression and not the noise. '''''Record the number of genes left in your electronic notebook.'''''
		+	#** Delete all of the data columns '''''EXCEPT''''' for the Average Log Fold change columns for each timepoint (for example, wt_AvgLogFC_t15, etc.).
		+	#** Rename the data columns with just the time and units (for example, 15m, 30m, etc.).
		+	#** Save your work. Then use ''Save As'' to save this spreadsheet as Text (Tab-delimited) (*.txt). Click OK to the warnings and close your file.
		+	#*** Note that you should turn on the file extensions if you have not already done so.
		+	# '''Now download and extract the STEM software.''' [http://www.cs.cmu.edu/~jernst/stem/ Click here to go to the STEM web site].
		+	#* Click on the [http://www.andrew.cmu.edu/user/zivbj/stemreg.html download link], register, and download the <code>stem.zip</code> file to your Desktop.
		+	#* Unzip the file. In Seaver 120, you can right click on the file icon and select the menu item ''7-zip > Extract Here''.
		+	#* This will create a folder called <code>stem</code>. Inside the folder, double-click on the <code>stem.jar</code> to launch the STEM program.
		+	<!--#** In Seaver 120, we encountered an issue where the program would not launch on the Windows XP machines due to a lack of memory. (Even though the computers have been upgraded to Windows 7, do this to launch the program.) To get around this problem, launch STEM from the command line.
		+	#*** Go to the start menu and click on ''Programs > Accessories > Command Prompt''.
		+	#*** You will need to navigate to the directory (folder) in which the STEM program resides. If you followed the instructions above and extracted the stem folder to the Desktop, type the following: <code>cd Desktop\stem</code> and press "Enter".
		+	#*** To launch the program then type: <code>java -mx512M -jar stem.jar -d defaults.txt</code> and press "Enter". This will launch the program with less memory allocated to it.-->
		+	# '''Running STEM'''
		+	## In section 1 (Expression Data Info) of the the main STEM interface window, click on the ''Browse...'' button to navigate to and select your file.
		+	##* Click on the radio button ''No normalization/add 0''.
		+	##* Check the box next to ''Spot IDs included in the data file''.
		+	## In section 2 (Gene Info) of the main STEM interface window, select ''Saccharomyces cerevisiae (SGD)'', from the drop-down menu for Gene Annotation Source. Select ''No cross references'', from the Cross Reference Source drop-down menu. Select ''No Gene Locations'' from the Gene Location Source drop-down menu.
		+	## In section 3 (Options) of the main STEM interface window, make sure that the Clustering Method says "STEM Clustering Method" and do not change the defaults for Maximum Number of Model Profiles or Maximum Unit Change in Model Profiles between Time Points.
		+	## In section 4 (Execute) click on the yellow Execute button to run STEM.
		+	# '''Viewing and Saving STEM Results'''
		+	## A new window will open called "All STEM Profiles (1)". Each box corresponds to a model expression profile. Colored profiles have a statistically significant number of genes assigned; they are arranged in order from most to least significant p value. Profiles with the same color belong to the same cluster of profiles. The number in each box is simply an ID number for the profile.
		+	##* Click on the button that says "Interface Options...". At the bottom of the Interface Options window that appears below where it says "X-axis scale should be:", click on the radio button that says "Based on real time". Then close the Interface Options window.
		+	##*Take a screenshot of this window (on a PC, simultaneously press the <code>Alt</code> and <code>PrintScreen</code> buttons to save the view in the active window to the clipboard) and paste it into a PowerPoint presentation to save your figures.
		+	## Click on each of the SIGNIFICANT profiles (the colored ones) to open a window showing a more detailed plot containing all of the genes in that profile.
		+	##* Take a screenshot of each of the individual profile windows and save the images in your PowerPoint presentation.
		+	##* At the bottom of each profile window, there are two yellow buttons "Profile Gene Table" and "Profile GO Table". For each of the profiles, click on the "Profile Gene Table" button to see the list of genes belonging to the profile. In the window that appears, click on the "Save Table" button and save the file to your desktop. Make your filename descriptive of the contents, e.g. "wt_profile#_genelist.txt", where you replace the number symbol with the actual profile number.
		+	##** Upload these files to the wiki and link to them on your individual journal page. (Note that it will be easier to zip all the files together and upload them as one file).
		+	##* For each of the significant profiles, click on the "Profile GO Table" to see the list of Gene Ontology terms belonging to the profile. In the window that appears, click on the "Save Table" button and save the file to your desktop. Make your filename descriptive of the contents, e.g. "wt_profile#_GOlist.txt", where you use "wt", "dGLN3", etc. to indicate the dataset and where you replace the number symbol with the actual profile number. At this point you have saved all of the primary data from the STEM software and it's time to interpret the results!
		+	##** Upload these files to the wiki and link to them on your individual journal page. (Note that it will be easier to zip all the files together and upload them as one file).
		+	# '''Analyzing and Interpreting STEM Results'''
		+	## Select '''''one''''' of the profiles you saved in the previous step for further intepretation of the data. I suggest that you choose one that has a pattern of up- or down-regulated genes at the cold shock timepoints. '''''Each member of your group should choose a different profile.''''' Answer the following:
		+	##* '''''Why did you select this profile? In other words, why was it interesting to you?'''''
		+	##*: I picked it randomly, don't have enough of an understanding to make a choice with any other reason.
		+	##* '''''How many genes belong to this profile?'''''
		+	##*: 114
		+	##* '''''How many genes were expected to belong to this profile?'''''
		+	##: 49.1
		+	##* '''''What is the p value for the enrichment of genes in this profile?''''' Bear in mind that we just finished computing p values to determine whether each individual gene had a significant change in gene expression at each time point. This p value determines whether the number of genes that show this particular expression profile across the time points is significantly more than expected.
		+	##*: 7.1 E-16
		+	##* Open the GO list file you saved for this profile in Excel. This list shows all of the Gene Ontology terms that are associated with genes that fit this profile. Select the third row and then choose from the menu Data > Filter > Autofilter. Filter on the "p-value" column to show only GO terms that have a p value of < 0.05. '''''How many GO terms are associated with this profile at p < 0.05?''''' The GO list also has a column called "Corrected p-value". This correction is needed because the software has performed thousands of significance tests. Filter on the "Corrected p-value" column to show only GO terms that have a corrected p value of < 0.05. '''''How many GO terms are associated with this profile with a corrected p value < 0.05?'''''
		+	##*: 264 and 73
		+	##* Select 6 Gene Ontology terms from your filtered list (either p < 0.05 or corrected p < 0.05).
		+	##*: cellular response to stimulus, protein binding, organophosphate ester transport, protein localization to organelle, and proteasomal protein catabolic process.
		+	##** Each member of the group will be reporting on his or her own cluster in your presentation next week. You should take care to choose terms that are the most significant, but that are also not too redundant. For example, "RNA metabolism" and "RNA biosynthesis" are redundant with each other because they mean almost the same thing.
		+	##**'''''Look up the definitions for each of the terms at [http://geneontology.org http://geneontology.org]. In your final presentation, you will discuss the biological interpretation of these GO terms. In other words, why does the cell react to cold shock by changing the expression of genes associated with these GO terms? Also, what does this have to do with the transcription factor that was deleted from your strain?'''''
		+	##** To easily look up the definitions, go to [http://geneontology.org http://geneontology.org].
		+	##** Copy and paste the GO ID (e.g. GO:0044848) into the search field at center top of the page called "Search GO Data".
		+	##** In the [http://amigo.geneontology.org/amigo/medial_search?q=GO%3A0044848 results] page, click on the button that says "Link to detailed information about <term>, in this case "biological phase"".
		+	##** The definition will be on the next results page, e.g. [http://amigo.geneontology.org/amigo/term/GO:0044848 here].
		+
		+	'''''This is the stopping point for the Week 10 Assignment.''''' We will pick up the next steps in the analysis in subsequent weeks.
	=Folder with PowerPoint and all files=		=Folder with PowerPoint and all files=
	[[media:Ebachoura-week10.zip\|Folder of Goodies]]		[[media:Ebachoura-week10.zip\|Folder of Goodies]]

Ebachour Week 10 - Revision history

Ebachour: Done with Week 10

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