Difference between revisions of "Emmatyrnauer Week 10"

From LMU BioDB 2017
Jump to: navigation, search
(→‎Conclusion: typo)
(→‎Files: link to YEASTRACT results)
 
(16 intermediate revisions by one other user not shown)
Line 1: Line 1:
 
==Electronic Notebook==
 
==Electronic Notebook==
 
=== Microarray Data Analysis Part 2: "High-level Analysis" ===
 
=== Microarray Data Analysis Part 2: "High-level Analysis" ===
−
 
−
We will be working on the protocols in class on Tuesday, October 31 and Thursday, November 2.  Whatever you do not finish in class will be homework to be completed by the Week 10 journal deadline.
 
−
 
−
==== Background ====
 
−
 
−
This is a list of steps required to analyze DNA microarray data.
 
−
 
−
#Quantitate the fluorescence signal in each spot
 
−
#Calculate the ratio of red/green fluorescence
 
−
#Log<sub>2</sub> transform the ratios
 
−
#* Steps 1-3 have been performed for you by the GenePix Pro software (which runs the microarray scanner).
 
−
#Normalize the ratios on each microarray slide
 
−
#Normalize the ratios for a set of slides in an experiment
 
−
#* Steps 4-5 was performed for you using a script in R, a statistics package (see: [https://openwetware.org/wiki/Dahlquist:Microarray_Data_Analysis_Workflow#Steps_4-5:_Within-_and_Between-chip_Normalization Microarray Data Analysis Workflow])
 
−
#* You will perform the following steps:
 
−
#Perform statistical analysis on the ratios
 
−
#Compare individual genes with known data
 
−
#* Steps 6-7 are performed in Microsoft Excel
 
−
#Pattern finding algorithms (clustering)
 
−
#Map onto biological pathways
 
−
#* We will use software called STEM for the clustering and mapping
 
−
# Identifying regulatory transcription factors responsible for observed changes in gene expression
 
−
# Dynamical systems modeling of the gene regulatory network ([http://kdahlquist.github.io/GRNmap/ GRNmap])
 
−
# Viewing modeling results in [http://dondi.github.io/GRNsight/ GRNsight]
 
−
 
 
==== Clustering and GO Term Enrichment with stem ====
 
==== Clustering and GO Term Enrichment with stem ====
−
 
+
# '''Preparing the microarray data file for loading into STEM.'''
−
# '''Prepare your microarray data file for loading into STEM.'''
+
#* I downloaded my Excel workbook that I used for my [[Week 8]] assignment.
−
#* Download your Excel workbook that you used for your [[Week 8]] assignment.
+
#* I inserted a new worksheet into my Excel workbook and named it "wt_stem".
−
#* Insert a new worksheet into your Excel workbook, and name it "wt_stem".
+
#* I selected all of the data from my "wt_ANOVA" worksheet and Pasted special > paste values into my "wt_stem" worksheet.
−
#* Select all of the data from your "(STRAIN)_ANOVA" worksheet and Paste special > paste values into your "(STRAIN)_stem" worksheet.
+
#** I made sure that the leftmost column had the column header "Master_Index" and renamed this column to "SPOT".  I made sure Column B was named "ID"and renamed this column to "Gene Symbol".  I deleted the column named "Standard_Name".
−
#** 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".
+
#** I filtered the data on the B-H corrected p value to be > 0.05 (that's '''greater than''' in this case).
−
#** Filter the data on the B-H corrected p value to be > 0.05 (that's '''greater than''' in this case).
+
#*** Once the data was filtered, I selected all of the rows (except for the header row) and deleted the rows by right-clicking and choosing "Delete Row" from the context menu.  I then undid the filter.  This ensured that only the genes with a "significant" change in expression, and not the noise, would be clustered. <span style="color:red">1822 genes were left </span>
−
#*** 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.''''' <code>2006</code>
+
#** I then deleted all of the data columns '''''EXCEPT''''' for the Average Log Fold change columns for each timepoint (for example, wt_AvgLogFC_t15, etc.).
−
#** Delete all of the data columns '''''EXCEPT''''' for the Average Log Fold change columns for each timepoint (for example, wt_AvgLogFC_t15, etc.).
+
#** I renamed the data columns with just the time and units (for example, 15m, 30m, etc.).
−
#** Rename the data columns with just the time and units (for example, 15m, 30m, etc.).
+
#** I saved my work and used ''Save As'' to save this spreadsheet as Text (Tab-delimited) (*.txt), clicked OK to the warnings and closed the file. ("wt_stem.txt" located in the compressed file: "Week10_filesforstem_wildtype_emmat.zip‎")
−
#** 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.
+
#*** I made sure all of the file extensions were turned on.
−
#*** Note that you should turn on the file extensions if you have not already done so.
+
# '''I downloaded and extracted the STEM software from [http://www.cs.cmu.edu/~jernst/stem/ here].'''
−
# '''Now download and extract the STEM software.'''  [http://www.cs.cmu.edu/~jernst/stem/ Click here to go to the STEM web site].
+
#* I clicked on the [http://www.andrew.cmu.edu/user/zivbj/stemreg.html download link], registered, and downloaded the <code>stem.zip</code> file to the Desktop.
−
#* 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.
+
#* I unziped the file.   
−
#* Unzip the file.  In Seaver 120, you can right click on the file icon and select the menu item ''7-zip > Extract Here''.
+
#* This created a folder called <code>stem</code>.  Inside the folder, I double-clicked on the <code>stem.jar</code> to launch the STEM program.
−
#* 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'''
 
# '''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.
+
## In section 1 (Expression Data Info) of the the main STEM interface window, I clicked on the ''Browse...'' button to navigate to and select my file.
−
##* Click on the radio button ''No normalization/add 0''.
+
##* I clicked on the radio button ''No normalization/add 0''.
−
##* Check the box next to ''Spot IDs included in the data file''.
+
##* I checked 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 2 (Gene Info) of the main STEM interface window, I selected ''Saccharomyces cerevisiae (SGD)'', from the drop-down menu for Gene Annotation Source.  I selected ''No cross references'', from the Cross Reference Source drop-down menu.  I selected ''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 3 (Options) of the main STEM interface window, I made sure that the Clustering Method said "STEM Clustering Method" and did 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.
+
## In section 4 (Execute) I clicked on the yellow Execute button to run STEM.
 
# '''Viewing and Saving STEM Results'''
 
# '''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.
+
## A new window opened called "All STEM Profiles (1)".  Each box corresponded to a model expression profile.  Colored profiles had a statistically significant number of genes assigned; they were arranged in order from most to least significant p value.  Profiles with the same color belonged to the same cluster of profiles.  The number in each box was 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.
+
##* I clicked on the button that said "Interface Options...".  At the bottom of the Interface Options window that appeared below where it said "X-axis scale should be:", I clicked on the radio button that said "Based on real time," then closed 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.
+
##*I took a screenshot of this window and pasted it into a PowerPoint presentation to save my 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.
+
## I clicked 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.
+
##* I took a screenshot of each of the individual profile windows and saved the images in my PowerPoint presentation (Wt_profileimage_presentation_emmat.pptx)
−
##* 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: wt_profile#_genelist.txt
+
##* At the bottom of each profile window, there were two yellow buttons "Profile Gene Table" and "Profile GO Table".  For each of the profiles, I clicked on the "Profile Gene Table" button to see the list of genes belonging to the profile.  In the window that appeared, I clicked on the "Save Table" button and saved the file to the desktop. I made sure the filename was descriptive of the contents: wt_profile#_genelist.txt
−
##** Compress and upload these files to the wiki and link to them on your individual journal page.  
+
##** I compressed and uploaded these files to the wiki and linked to them on my individual journal page. ("wt_profilenumber_genelist_emmat" located in compressed file: "Week10_filesforstem_wildtype_emmat.zip‎")
−
##* 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: "wt_profile#_GOlist.txt. At this point you have saved all of the primary data from the STEM software and it's time to interpret the results!
+
##* For each of the significant profiles, I clicked on the "Profile GO Table" to see the list of Gene Ontology terms belonging to the profile.  In the window that appeared, I clicked on the "Save Table" button and saved the file to the desktop.  I made the filename descriptive of the contents: wt_profile#_GOlist.txt. At this point I had saved all of the primary data from the STEM software and began interpretation of 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).
+
##** I compressed and uploaded these files to the wiki and linked to them on my individual journal page. ("wt_profilenumber_GOlist_emmat" located in compressed file: "Week10_filesforstem_wildtype_emmat.zip‎")
 
# '''Analyzing and Interpreting STEM Results'''
 
# '''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:
+
## I selected one of the profiles I saved in the previous step for further interpretation of the data.  
−
##* '''''Why did you select this profile?  In other words, why was it interesting to you?''''' <span style="color:red">I chose profile 45 because it shows a general trend of down regulation of genes at the cold shock time points.</span>
+
##* '''''Why did you select this profile?  In other words, why was it interesting to you?'''''  
−
##* '''''How many genes belong to this profile?''''' <span style="color:red">580 genes belong to this profile.</span>
+
##**<span style="color:red">I chose profile 45 because it shows a general trend of up regulation of genes at the cold shock time point.</span>
−
##* '''''How many genes were expected to belong to this profile?''''' <span style="color:red">52.7 genes were expected to belong to this profile.</span>
+
##* '''''How many genes belong to this profile?'''''  
−
##* '''''What is the p value for the enrichment of genes in this profile?''''' <span style="color:red">0.00 is the p-value for the enrichment of genes in this profile.</span> 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.
+
##**<span style="color:red">549 genes belong to this profile.</span>
−
##* 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?''''' <span style="color:red">247 GO terms are associated with profile 45. </span> 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?''''' <span style="color:red">28 GO terms are associated with profile 45 with a corrected p value < 0.05</span>
+
##* '''''How many genes were expected to belong to this profile?'''''  
−
##* Select 6 Gene Ontology terms from your filtered list of corrected p < 0.05.   
+
##**<span style="color:red">47.1 genes were expected to belong to this profile.</span>
−
##** 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.
+
##* '''''What is the p value for the enrichment of genes in this profile?''''' (This p value determines whether the number of genes that show this particular expression profile across the time points is significantly more than expected.)
−
##*** Note whether the same GO terms are showing up in multiple clusters.
+
##**<span style="color:red">0.00 is the p-value for the enrichment of genes in this profile.</span>  
−
##**'''''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 being deleted (for the Δgln3 and Δswi4 groups)?'''''
+
##* I opened the GO list file I saved for this profile in Excel.  This list shows all of the Gene Ontology terms that are associated with genes that fit this profile.  I selected the third row and then chose from the menu Data > Filter > Autofilter.  I filtered 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?''''' <span style="color:red">240 GO terms are associated with profile 45 at p<0.05. </span> The GO list also has a column called "Corrected p-value".  This correction is needed because the software has performed thousands of significance tests.  I filtered 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?''''' <span style="color:red">39 GO terms are associated with profile 45 with a corrected p value < 0.05.</span>
−
##** To easily look up the definitions, go to [http://geneontology.org http://geneontology.org].
+
##* I selected 6 Gene Ontology terms from my filtered list of corrected p < 0.05.   
−
##** Copy and paste the GO ID (e.g. GO:0044848) into the search field at center top of the page called "Search GO Data".
+
##**'''''I looked up the definitions for each of the terms at [http://geneontology.org http://geneontology.org].  In my final presentation, I 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 being deleted (for the Δgln3 and Δswi4 groups)?'''''
−
##** 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"".  
+
##** To look up the definitions, I went to [http://geneontology.org http://geneontology.org].
−
##** The definition will be on the next results page, e.g. [http://amigo.geneontology.org/amigo/term/GO:0044848 here].
+
##** I copied and pasted the GO ID (e.g. GO:0044848) into the search field at center top of the page called "Search GO Data".
−
##***<span style="color:red">'''ribosome assembly''': The aggregation, arrangement and bonding together of the mature ribosome and of its subunits</span> [http://amigo.geneontology.org/amigo/term/GO:0042255]
+
##** In the [http://amigo.geneontology.org/amigo/medial_search?q=GO%3A0044848 results] page, I clicked on the button that says "Link to detailed information about <term>, in this case "biological phase"".  
−
##***<span style="color:red">'''RNA modification''': The covalent alteration of one or more nucleotides within an RNA molecule to produce an RNA molecule with a sequence that differs from that coded genetically</span> [http://amigo.geneontology.org/amigo/term/GO:0009451]
+
##** The definition was on the next results page, e.g. [http://amigo.geneontology.org/amigo/term/GO:0044848 here].
−
##***<span style="color:red">'''ncRNA catabolic process''': The chemical reactions and pathways resulting in the breakdown of non-coding RNA transcripts (ncRNAs). Includes the breakdown of cryptic unstable transcripts</span> [http://amigo.geneontology.org/amigo/term/GO:0034661]
+
##***<span style="color:red">'''ribosome assembly''' (GO:0042255): The aggregation, arrangement and bonding together of the mature ribosome and of its subunits</span> [http://amigo.geneontology.org/amigo/term/GO:0042255]
−
##***<span style="color:red">'''intracellular membrane-bounded organelle''': Organized structure of distinctive morphology and function, bounded by a single or double lipid bilayer membrane and occurring within the cell. Includes the nucleus, mitochondria, plastids, vacuoles, and vesicles. Excludes the plasma membrane</span> [http://amigo.geneontology.org/amigo/term/GO:0043231]
+
##***<span style="color:red">'''RNA modification''' (GO:0009451): The covalent alteration of one or more nucleotides within an RNA molecule to produce an RNA molecule with a sequence that differs from that coded genetically</span> [http://amigo.geneontology.org/amigo/term/GO:0009451]
−
##***<span style="color:red">'''tRNA metabolic process''': The chemical reactions and pathways involving tRNA, transfer RNA, a class of relatively small RNA molecules responsible for mediating the insertion of amino acids into the sequence of nascent polypeptide chains during protein synthesis. Transfer RNA is characterized by the presence of many unusual minor bases, the function of which has not been completely established</span> [http://amigo.geneontology.org/amigo/term/GO:0006399]
+
##***<span style="color:red">'''ncRNA catabolic process''' (GO:0034661): The chemical reactions and pathways resulting in the breakdown of non-coding RNA transcripts (ncRNAs). Includes the breakdown of cryptic unstable transcripts</span> [http://amigo.geneontology.org/amigo/term/GO:0034661]
−
##***<span style="color:red">'''ribosomal subunit export from nucleus''': The directed movement of a ribosomal subunit from the nucleus into the cytoplasm. </span> [http://amigo.geneontology.org/amigo/term/GO:0000054]
+
##***<span style="color:red">'''intracellular membrane-bounded organelle''' (GO:0043231): Organized structure of distinctive morphology and function, bounded by a single or double lipid bilayer membrane and occurring within the cell. Includes the nucleus, mitochondria, plastids, vacuoles, and vesicles. Excludes the plasma membrane</span> [http://amigo.geneontology.org/amigo/term/GO:0043231]
−
 
+
##***<span style="color:red">'''nucleoplasm''' (GO:0005654): That part of the nuclear content other than the chromosomes or the nucleolus.</span> [http://amigo.geneontology.org/amigo/term/GO:0005654]
 +
##***<span style="color:red">'''ribosomal subunit export from nucleus''' (GO:0000054): The directed movement of a ribosomal subunit from the nucleus into the cytoplasm. </span> [http://amigo.geneontology.org/amigo/term/GO:0000054]
 +
##**** '''Why does the cell react to cold shock by changing the expression of genes associated with these GO terms?''' The activity of these genes associated with these GO terms may increase to maintain viability of the cell in a highly-stressed environment. Furthermore, these genes may increase in expression to allow for greater efficiency of the cell during harsh conditions so that unnecessary energy is not expended.
 
====Files====
 
====Files====
 
#Updated excel spreadsheet: [[Media:Wt_Microarraydata_ET.zip]]
 
#Updated excel spreadsheet: [[Media:Wt_Microarraydata_ET.zip]]
 
#Updated powerpoint presentation: [[Media:Wt_profileimage_presentation_emmat.pptx]]
 
#Updated powerpoint presentation: [[Media:Wt_profileimage_presentation_emmat.pptx]]
 
#File used to run stem, gene list tables, GO list tables: [[Media:Week10_filesforstem_wildtype_emmat.zip‎]]
 
#File used to run stem, gene list tables, GO list tables: [[Media:Week10_filesforstem_wildtype_emmat.zip‎]]
 +
#YEASTRACT rank by TF results: [[Media:YEASTRACT_results_ET_20171130.xlsx | YEASTRACT_results_ET_20171130.xlsx]]
  
 
====Conclusion====
 
====Conclusion====
−
For the assignment this week, we did clustering and GO term enrichment with STEM, downloaded and ran the STEM software using an updated excel spreadsheet, obtained figures and results from the software, and analyzed and interpreted the STEM results. A new worksheet was created in the excel workbook from week 8 that involved renaming and filtering data from the wt_ANOVA worksheet. Using this updated file, STEM created figures and tables representing clusters/profiles of genes with similar responses in terms of expression following cold shock. One profile was chosen (45) for further analysis in terms of the identification of genes associated with different p-values within the profile, and 6 GO terms were selected from the filtered list of corrected p<0.05 and looked up with http://geneontology.org.
+
For the assignment this week, we did clustering and GO term enrichment with STEM, downloaded and ran the STEM software using an updated excel spreadsheet, obtained figures and results from the software, and analyzed and interpreted the STEM results. A new worksheet was created in the excel workbook from week 8 that involved renaming and filtering data from the wt_ANOVA worksheet. Using this updated file, STEM created figures and tables representing clusters/profiles of genes with similar responses in terms of expression following cold shock. One profile was chosen (45) for further analysis in terms of the identification of genes associated with different p-values within the profile, and 6 GO terms were selected from the filtered list of corrected p<0.05 and looked up with http://geneontology.org. Based on the GO terms that were designated for each cluster, I hypothesize that genes which code for parts of the cell which are needed for cell survival/cell rescue will be upregulated. On the other hand, genes involved in processes that aren't required for cell survival may be downregulated to conserve energy.
  
 
==Acknowledgements==
 
==Acknowledgements==
−
#I worked with my homework partner Eddie Azinge during class and over text.
+
#I worked with my homework partner [[User:cazinge|Eddie Azinge]] during class and over text.
 
#Dr. Dahlquist for teaching and assisting us with the data analysis
 
#Dr. Dahlquist for teaching and assisting us with the data analysis
−
#Microsoft Excel to allow for statistical analysis
+
# I copied and modified the instructions from the [[Week 10]] assignment page.
 
While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.
 
While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.
 
[[User:Emmatyrnauer|Emmatyrnauer]] ([[User talk:Emmatyrnauer|talk]]) 15:14, 31 October 2017 (PDT)
 
[[User:Emmatyrnauer|Emmatyrnauer]] ([[User talk:Emmatyrnauer|talk]]) 15:14, 31 October 2017 (PDT)
  
 
==References==
 
==References==
−
#Gene Ontology Consortium. (2017). The Gene Ontology. Retrieved November 6, 2017, from http://geneontology.org  
+
#Gene Ontology Consortium. (2017). The Gene Ontology. Retrieved November 19, 2017, from http://geneontology.org  
−
#LMU BioDB 2017. (2017). Week 10. Retrieved November 4, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10
+
#*Ribosome assembly. The Gene Ontology. Retrieved November 19, 2017, from http://amigo.geneontology.org/amigo/term/GO:0042255
 +
#*RNA modification. The Gene Ontology. Retrieved November 19, 2017, from http://amigo.geneontology.org/amigo/term/GO:0009451
 +
#*ncRNA catabolic process. The Gene Ontology. Retrieved November 19, 2017, from http://amigo.geneontology.org/amigo/term/GO:0034661
 +
#* Nucleoplasm. The Gene Ontology. Retrieved November 19, 2017, from http://amigo.geneontology.org/amigo/term/GO:0005654
 +
#*Intracellular membrane-bounded organelle. The Gene Ontology. Retrieved November 19, 2017, http://amigo.geneontology.org/amigo/term/GO:0043231
 +
#*Ribosomal subunit export from nucleus. The Gene Ontology. Retrieved November 19, 2017, from http://amigo.geneontology.org/amigo/term/GO:0000054
 +
#LMU BioDB 2017. (2017). Week 10. Retrieved November 19, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10
 +
#Short Time-series Expression Miner (STEM). (2006). Retrieved November 19, 2017, from http://www.cs.cmu.edu/~jernst/stem/
 
{{Emmatyrnauer}}
 
{{Emmatyrnauer}}

Latest revision as of 23:03, 30 November 2017

Electronic Notebook

Microarray Data Analysis Part 2: "High-level Analysis"

Clustering and GO Term Enrichment with stem

  1. Preparing the microarray data file for loading into STEM.
    • I downloaded my Excel workbook that I used for my Week 8 assignment.
    • I inserted a new worksheet into my Excel workbook and named it "wt_stem".
    • I selected all of the data from my "wt_ANOVA" worksheet and Pasted special > paste values into my "wt_stem" worksheet.
      • I made sure that the leftmost column had the column header "Master_Index" and renamed this column to "SPOT". I made sure Column B was named "ID"and renamed this column to "Gene Symbol". I deleted the column named "Standard_Name".
      • I filtered the data on the B-H corrected p value to be > 0.05 (that's greater than in this case).
        • Once the data was filtered, I selected all of the rows (except for the header row) and deleted the rows by right-clicking and choosing "Delete Row" from the context menu. I then undid the filter. This ensured that only the genes with a "significant" change in expression, and not the noise, would be clustered. 1822 genes were left
      • I then deleted all of the data columns EXCEPT for the Average Log Fold change columns for each timepoint (for example, wt_AvgLogFC_t15, etc.).
      • I renamed the data columns with just the time and units (for example, 15m, 30m, etc.).
      • I saved my work and used Save As to save this spreadsheet as Text (Tab-delimited) (*.txt), clicked OK to the warnings and closed the file. ("wt_stem.txt" located in the compressed file: "Week10_filesforstem_wildtype_emmat.zip‎")
        • I made sure all of the file extensions were turned on.
  2. I downloaded and extracted the STEM software from here.
    • I clicked on the download link, registered, and downloaded the stem.zip file to the Desktop.
    • I unziped the file.
    • This created a folder called stem. Inside the folder, I double-clicked on the stem.jar to launch the STEM program.
  3. Running STEM
    1. In section 1 (Expression Data Info) of the the main STEM interface window, I clicked on the Browse... button to navigate to and select my file.
      • I clicked on the radio button No normalization/add 0.
      • I checked the box next to Spot IDs included in the data file.
    2. In section 2 (Gene Info) of the main STEM interface window, I selected Saccharomyces cerevisiae (SGD), from the drop-down menu for Gene Annotation Source. I selected No cross references, from the Cross Reference Source drop-down menu. I selected No Gene Locations from the Gene Location Source drop-down menu.
    3. In section 3 (Options) of the main STEM interface window, I made sure that the Clustering Method said "STEM Clustering Method" and did not change the defaults for Maximum Number of Model Profiles or Maximum Unit Change in Model Profiles between Time Points.
    4. In section 4 (Execute) I clicked on the yellow Execute button to run STEM.
  4. Viewing and Saving STEM Results
    1. A new window opened called "All STEM Profiles (1)". Each box corresponded to a model expression profile. Colored profiles had a statistically significant number of genes assigned; they were arranged in order from most to least significant p value. Profiles with the same color belonged to the same cluster of profiles. The number in each box was simply an ID number for the profile.
      • I clicked on the button that said "Interface Options...". At the bottom of the Interface Options window that appeared below where it said "X-axis scale should be:", I clicked on the radio button that said "Based on real time," then closed the Interface Options window.
      • I took a screenshot of this window and pasted it into a PowerPoint presentation to save my figures.
    2. I clicked 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.
      • I took a screenshot of each of the individual profile windows and saved the images in my PowerPoint presentation (Wt_profileimage_presentation_emmat.pptx)
      • At the bottom of each profile window, there were two yellow buttons "Profile Gene Table" and "Profile GO Table". For each of the profiles, I clicked on the "Profile Gene Table" button to see the list of genes belonging to the profile. In the window that appeared, I clicked on the "Save Table" button and saved the file to the desktop. I made sure the filename was descriptive of the contents: wt_profile#_genelist.txt
        • I compressed and uploaded these files to the wiki and linked to them on my individual journal page. ("wt_profilenumber_genelist_emmat" located in compressed file: "Week10_filesforstem_wildtype_emmat.zip‎")
      • For each of the significant profiles, I clicked on the "Profile GO Table" to see the list of Gene Ontology terms belonging to the profile. In the window that appeared, I clicked on the "Save Table" button and saved the file to the desktop. I made the filename descriptive of the contents: wt_profile#_GOlist.txt. At this point I had saved all of the primary data from the STEM software and began interpretation of the results.
        • I compressed and uploaded these files to the wiki and linked to them on my individual journal page. ("wt_profilenumber_GOlist_emmat" located in compressed file: "Week10_filesforstem_wildtype_emmat.zip‎")
  5. Analyzing and Interpreting STEM Results
    1. I selected one of the profiles I saved in the previous step for further interpretation of the data.
      • Why did you select this profile? In other words, why was it interesting to you?
        • I chose profile 45 because it shows a general trend of up regulation of genes at the cold shock time point.
      • How many genes belong to this profile?
        • 549 genes belong to this profile.
      • How many genes were expected to belong to this profile?
        • 47.1 genes were expected to belong to this profile.
      • What is the p value for the enrichment of genes in this profile? (This p value determines whether the number of genes that show this particular expression profile across the time points is significantly more than expected.)
        • 0.00 is the p-value for the enrichment of genes in this profile.
      • I opened the GO list file I saved for this profile in Excel. This list shows all of the Gene Ontology terms that are associated with genes that fit this profile. I selected the third row and then chose from the menu Data > Filter > Autofilter. I filtered 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? 240 GO terms are associated with profile 45 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. I filtered 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? 39 GO terms are associated with profile 45 with a corrected p value < 0.05.
      • I selected 6 Gene Ontology terms from my filtered list of corrected p < 0.05.
        • I looked up the definitions for each of the terms at http://geneontology.org. In my final presentation, I 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 being deleted (for the Δgln3 and Δswi4 groups)?
        • To look up the definitions, I went to http://geneontology.org.
        • I copied and pasted the GO ID (e.g. GO:0044848) into the search field at center top of the page called "Search GO Data".
        • In the results page, I clicked on the button that says "Link to detailed information about <term>, in this case "biological phase"".
        • The definition was on the next results page, e.g. here.
          • ribosome assembly (GO:0042255): The aggregation, arrangement and bonding together of the mature ribosome and of its subunits [1]
          • RNA modification (GO:0009451): The covalent alteration of one or more nucleotides within an RNA molecule to produce an RNA molecule with a sequence that differs from that coded genetically [2]
          • ncRNA catabolic process (GO:0034661): The chemical reactions and pathways resulting in the breakdown of non-coding RNA transcripts (ncRNAs). Includes the breakdown of cryptic unstable transcripts [3]
          • intracellular membrane-bounded organelle (GO:0043231): Organized structure of distinctive morphology and function, bounded by a single or double lipid bilayer membrane and occurring within the cell. Includes the nucleus, mitochondria, plastids, vacuoles, and vesicles. Excludes the plasma membrane [4]
          • nucleoplasm (GO:0005654): That part of the nuclear content other than the chromosomes or the nucleolus. [5]
          • ribosomal subunit export from nucleus (GO:0000054): The directed movement of a ribosomal subunit from the nucleus into the cytoplasm. [6]
            • Why does the cell react to cold shock by changing the expression of genes associated with these GO terms? The activity of these genes associated with these GO terms may increase to maintain viability of the cell in a highly-stressed environment. Furthermore, these genes may increase in expression to allow for greater efficiency of the cell during harsh conditions so that unnecessary energy is not expended.

Files

  1. Updated excel spreadsheet: Media:Wt_Microarraydata_ET.zip
  2. Updated powerpoint presentation: Media:Wt_profileimage_presentation_emmat.pptx
  3. File used to run stem, gene list tables, GO list tables: Media:Week10_filesforstem_wildtype_emmat.zip‎
  4. YEASTRACT rank by TF results: YEASTRACT_results_ET_20171130.xlsx

Conclusion

For the assignment this week, we did clustering and GO term enrichment with STEM, downloaded and ran the STEM software using an updated excel spreadsheet, obtained figures and results from the software, and analyzed and interpreted the STEM results. A new worksheet was created in the excel workbook from week 8 that involved renaming and filtering data from the wt_ANOVA worksheet. Using this updated file, STEM created figures and tables representing clusters/profiles of genes with similar responses in terms of expression following cold shock. One profile was chosen (45) for further analysis in terms of the identification of genes associated with different p-values within the profile, and 6 GO terms were selected from the filtered list of corrected p<0.05 and looked up with http://geneontology.org. Based on the GO terms that were designated for each cluster, I hypothesize that genes which code for parts of the cell which are needed for cell survival/cell rescue will be upregulated. On the other hand, genes involved in processes that aren't required for cell survival may be downregulated to conserve energy.

Acknowledgements

  1. I worked with my homework partner Eddie Azinge during class and over text.
  2. Dr. Dahlquist for teaching and assisting us with the data analysis
  3. I copied and modified the instructions from the Week 10 assignment page.

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source. Emmatyrnauer (talk) 15:14, 31 October 2017 (PDT)

References

  1. Gene Ontology Consortium. (2017). The Gene Ontology. Retrieved November 19, 2017, from http://geneontology.org
  2. LMU BioDB 2017. (2017). Week 10. Retrieved November 19, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Week_10
  3. Short Time-series Expression Miner (STEM). (2006). Retrieved November 19, 2017, from http://www.cs.cmu.edu/~jernst/stem/

Links

  1. My User Page
  2. List of Assignments
  3. List of Journal Entries
  4. List of Shared Journal Entries
Retrieved from "https://xmlpipedb.lmucs.io/biodb/fall2017/index.php?title=Emmatyrnauer_Week_10&oldid=5237"