Claudia Campos Week 9

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Filtered GO terms

Electronic Lab Notebook

  • Launch the GenMAPP Program.
  • Look in the lower, left-hand corner of the main GenMAPP Drafting Board window to see the name of the Gene Database that is loaded. If this is not the correct Gene Database or it says "No Gene Database", then go to the Data > Choose Gene Database menu item to select the Vc-Std_External_20101022.gdb Gene Database to perform the analysis.
  • Select the Data menu from the main Drafting Board window and choose Expression Dataset Manager from the drop-down list. The Expression Dataset Manager window will open.
  • Select New Dataset from the Expression Datasets menu. Select the tab-delimited text file that you formatted for GenMAPP (.txt) in the procedure above from the file dialog box that appears.
  • The Data Type Specification window will appear. GenMAPP is expecting that you are providing numerical data. NO boxes are checked.
  • Allow the Expression Dataset Manager to convert your data. When the process is complete, the converted dataset will be active in the Expression Dataset Manager window and the file will be saved in the same folder the raw data file was in, named the same except with a .gex extension; for example, MyExperiment.gex.
  • A message may appear saying that the Expression Dataset Manager could not convert one or more lines of data. Lines that generate an error during the conversion of a raw data file are not added to the Expression Dataset. Instead, an exception file is created. The exception file is given the same name as your raw data file with .EX before the extension (e.g., MyExperiment.EX.txt). The exception file will contain all of your raw data, with the addition of a column named ~Error~. This column contains either error messages or, if the program finds no errors, a single space character.
  • Color Sets contain the instructions to GenMAPP for displaying data from an Expression Dataset on MAPPs. Create a Color Set by filling in the following different fields in the Color Set area of the Expression Dataset Manager: a name for the Color Set, the gene value, and the criteria that determine how a gene object is colored on the MAPP. Enter a name in the Color Set Name field that is 20 characters or fewer.

The Gene Value is the data displayed next to the gene box on a MAPP. Select the column of data to be used as the Gene Value from the drop down list or select [none]. We will use "Avg_LogFC_all" for the Vibrio dataset you just created.

  • Activate the Criteria Builder by clicking the New button.
  • Enter a name for the criterion in the Label in Legend field.
  • Choose a color for the criterion by left-clicking on the Color box. *Choose a color from the Color window that appears and click OK.
  • State the criterion for color-coding a gene in the Criterion field:
"Increased" will be [Avg_LogFC_all] > 0.25 AND [Pvalue] < 0.05 
"Decreased" will be [Avg_LogFC_all] < -0.25 AND [Pvalue] < 0.05. 
  • Add the criterion entry (label, criterion, and color) to the Criteria List by clicking the Add button.
  • Save the entire Expression Dataset by selecting Save from the Expression Dataset menu. Changes made to a Color Set are not saved until you do this.
  • Exit the Expression Dataset Manager to view the Color Sets on a MAPP. Choose Exit from the Expression Dataset menu or click the close box in the upper right hand corner of the window.
  • Launch the MAPPFinder program (or from within GenMAPP, select Tools > MAPPFinder.
  • Click on the button "Calculate New Results".
  • Click on "Find File" and choose the your Expression Dataset file, for example, "MyDataset.gex", and click OK.
  • Choose the Color Set and Criteria with which to filter the data. Click on either the "Increased" and "Decreased" criteria in the right-hand box, depending on which one your group is doing.
  • Check the boxes next to "Gene Ontology" and "p value".
  • Click the "Browse" button and create a meaningful filename for your results.
  • Click "Run MAPPFinder". The analysis will take several minutes. It may look like the computer is stalled; be patient, it will eventually start running.
  • When the results have been calculated, a Gene Ontology browser will open showing your results. All of the Gene Ontology terms that have at least 3 genes measured and a p value of less than 0.05 will be highlighted yellow. A term with a p value less than 0.05 is considered a "significant" result. Browse through the tree to see your results.

To see a list of the most significant Gene Ontology terms, click on the menu item "Show Ranked List".

  • Click on one of the GO terms that are associated with one of the genes you looked up in the previous step. A MAPP will open listing all of the genes (as boxes) associated with that GO term. The genes named within the map are based on the UniProt identification system. To match the gene of interest to its identification go to the UniProt site and type in your gene ID into the search bar. Moreover, the genes on the MAPP will be color-coded with the gene expression data from the microarray experiment.
  • Double-click on the gene box. This will open a Internet Explorer window called the "Backpage" for this gene.
  • Launch Microsoft Excel. Open the copies of the .txt files in Excel
  • Look at the top of the spreadsheet. There are rows of information that give you the background information on how MAPPFinder made the calculations.
  • Filter the list as follows:
Z Score (in column N) greater than 2
PermuteP (in column O) less than 0.05
  • Save your changes to an Excel spreadsheet. Select File > Save As and select Excel workbook (.xls) from the drop-down menu. Your filter settings won’t be saved in a .txt file.


New: 121 errors

Old: 772 errors

Top 10:

  1. Branched chain family amino acid metabolic processes
  2. Branched chain family amino acid biosynthetic process
  3. IMP metabolic process
  4. IMP biosynthetic process
  5. Purine nucleoside monophosphate biosynthetic process
  6. Purine ribonucleoside monophosphate biosynthetic process
  7. Purine nucleoside monophosphate metabolic process
  8. Arginine metabolic process
  9. Cellular nitrogen compound biosynthetic process
  10. Ribonucleoside monophosphate metabolic process

Comparision: None of the genes in my top 10 matched the genes in Evan's top 10 because I am using the new version and it's been updated. Evan has the older version, so those updates don't exist.

VC0028: branched chain family amino acid biosynthetic process, cellular amino acid biosynthetic process, metabolic process, metal ion binding, iron-sulfur cluster binding, 4 iron 4 sulfur cluster binding, catalytic activity, lyase activity, dihydroxy-acid dehydratase activity

VC0941: glycine metabolic process, l-serine metabolic process, one-carbon metabolic process, cytoplasm, pyridoxal phosphate binding, catalytic activity, transferase activity, glycine hydroxymethyltransferase activity

VC0869: glutamine metabolic process, purine nucleotide biosynthetic process, 'de novo' IMP biosynthetic process, cytoplasm, nucleotide binding, ATP binding, catalytic activity, ligase activity, phosphoribosylformylglycinamidine synthase activity

VC0051: purine nucleotide biosynthetic process, 'de novo' IMP biosynthetic process, nucleotide binding, ATP binding, catalytic activity, lyase activity, carboxy-lyase activity, phosphoribosylaminoimidazole carboxylase activity

VC0647: mRNA catabolic process, RNA processing, cytoplasm, mitochondrion, RNA binding, 3'-5'-exoribonuclease activity, transferase activity, nucleotidyltransferase activity, polyribonucleotide nucleotidyltransferase activity

VC0468: glutathione biosynthetic process, metal ion binding, nucleotide binding, ATP binding, catalytic activity, ligase activity, glutathione synthase activity

VC2350: deoxyribonucleotide catabolic process, metabolic process, cytoplasm, catalytic activity, lyase activity, deoxyribose-phosphate aldolase activity

VCA0583: transport, outer membrane-bound periplasmic space, transporter activity

Comparison: The GO terms associated with the genes were completely different than Evan's. His older version only had GO terms for two genes, whereas I had a full list for every gene.

The gene I chose was VC2350 whose protein name is Deoxyribose-phosphate aldolase and it didn't change significantly. This is an enzyme that catalyzes the cleaving of carbon-carbon bonds.