** This may take a few minutes depending on the size of the dataset and the computer’s memory and processor speed. 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.
 
** This may take a few minutes depending on the size of the dataset and the computer’s memory and processor speed. 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.
 
** 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.
*** '''121 errors.'''
   
*** '''Record the number of errors.  For your journal assignment, open the .EX.txt file and use the Data > Filter > Autofilter function to determine what the errors were for the rows that were not converted.  Record this information in your individual journal page.'''
 
*** '''Record the number of errors.  For your journal assignment, open the .EX.txt file and use the Data > Filter > Autofilter function to determine what the errors were for the rows that were not converted.  Record this information in your individual journal page.'''
 +
**** 121 errors. The only apparent error is "Gene not found in OrderedLocusNames or any related system."
 
*** '''It is likely that you will have a different number of errors than your partner who is using a different version of the ''Vibrio cholerae'' Gene Database.  Which of you has more errors?  Why do you think that is?  Record your answers in your journal page.'''
 
*** '''It is likely that you will have a different number of errors than your partner who is using a different version of the ''Vibrio cholerae'' Gene Database.  Which of you has more errors?  Why do you think that is?  Record your answers in your journal page.'''
 
*** '''Upload your exceptions file:  <code>EX.txt</code> to your wiki page.
 
*** '''Upload your exceptions file:  <code>EX.txt</code> to your wiki page.
 +
**** My partner has more errors than I do, likely because the database is less up-to-date relative to the microarray data.
    
==Protocol - 10/22/15==
 
==Protocol - 10/22/15==
 
** Because this data compares lab-grown and patient-derived gene expression of the parasite, the genes which had lowered expressions between the two will be those that are repressed during pathogenic behavior. In the filtered GO term list, two major themes are glucose metabolism and protein synthesis (the broadest applicable terms in the list being "glucose metabolic process" and "cellular protein metabolic process"). Also prevalent are nucleotide processes ("DNA modification"). Glucose metabolism relates to pathogenicity because the bacterium may need to conserve glucose in the hostile environment that is a host. Consequently, it must also slow down its protein synthesis, which is quite energetically costly, requiring two ATP equivalents per peptide bond, not to mention other processes such as tRNA activation. In potentially harsh environments, both glucose catabolism and protein synthesis will conceivably be repressed. The nucleotide processes may be related to the slowing of cell division. Again, in energetically scarce environments, cell division must be de-prioritized, which could coincide with lowered expression of the corresponding nucleotide processes. There were a few other miscellaneous terms on the list, such as "lipopolysaccharide process." One reason a bacterium may want to reduce cell surface markers is to evade the immune system of the host.
 
** Because this data compares lab-grown and patient-derived gene expression of the parasite, the genes which had lowered expressions between the two will be those that are repressed during pathogenic behavior. In the filtered GO term list, two major themes are glucose metabolism and protein synthesis (the broadest applicable terms in the list being "glucose metabolic process" and "cellular protein metabolic process"). Also prevalent are nucleotide processes ("DNA modification"). Glucose metabolism relates to pathogenicity because the bacterium may need to conserve glucose in the hostile environment that is a host. Consequently, it must also slow down its protein synthesis, which is quite energetically costly, requiring two ATP equivalents per peptide bond, not to mention other processes such as tRNA activation. In potentially harsh environments, both glucose catabolism and protein synthesis will conceivably be repressed. The nucleotide processes may be related to the slowing of cell division. Again, in energetically scarce environments, cell division must be de-prioritized, which could coincide with lowered expression of the corresponding nucleotide processes. There were a few other miscellaneous terms on the list, such as "lipopolysaccharide process." One reason a bacterium may want to reduce cell surface markers is to evade the immune system of the host.
 
* '''There is one other file you need to save to your journal page.  It has a .gmf extension and should be in the same fold as the .gex file that you created with the GenMAPP Expression Dataset Manager.  You will need this file to re-open your results in MAPPFinder.'''
 
* '''There is one other file you need to save to your journal page.  It has a .gmf extension and should be in the same fold as the .gex file that you created with the GenMAPP Expression Dataset Manager.  You will need this file to re-open your results in MAPPFinder.'''
 +
 +
==Conclusion==
 +
 +
In this exercise, we analyzed microarray data taken from laboratory and patient-derived ''Vibrio cholera'' to investigate into which genes are involved in pathogenic behavior. First, we scaled and centered the fold change data. Then, we performed statistical analysis, calculating undajusted, Benjamini-Hochberg and Bonferroni P-values. We used the unadjusted P-value to create an expression dataset in GenMAPP, which used an existing gene database for ''V. cholera'' to indicate which gene ontologies (groups of genes with related functions) were increased and decreased (decreased for my group) during pathogenesis. While these genes differed depending on whether the 2009 or 2010 gene database was used, three main ontology categories that saw decreased expression were glucose metabolism, protein synthesis and DNA processes. Additionally, we compared our data against Merrel ''et al.'' suggestions of genes supposedly involved in pathogenesis, however, our data was quite different.
    
==Files==
 
==Files==
    
*This protocol was taken from Dr. Dahlquist's OpenWetware page.
 
*This protocol was taken from Dr. Dahlquist's OpenWetware page.
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