Difference between revisions of "February 2, 2016"

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== Classwork ==   
 
== Classwork ==   
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'''Today in class, we shared group findings from [[January 28, 2016]]:''' 
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#Blast the overrepresented sequences 
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*Blast groups found mostly mitochondrial or ribosomal genes. 
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*Intestine blast group found an amino transferase gene that may be of interest later. 
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*Liver blast group found an anti-hemorage gene that may be of interest later. 
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 +
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#Attempt to access the list of genes (SRP-0151827) mentioned in the Andrew et al. (2015) study 
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*We can blast our sequences against the Andrew et al. (2015) library. 
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*We have the potential to download the entire library with instructions on the website, but do not understand how to use the software/programs required to do so. 
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*We found a toolkit that allows us to download one sequence at a time. 
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*We can blast within a run. 
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 +
 
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#Add numbers to label proteins of "unknown function" in our reads 
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*Dylan and Dustin made a file that removed duplicate names from our runs. 
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*Dr. Campbell and Dr. Heyer used their file and got gene mapping results! 
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 +
 +
#Normalize relative abundance of transcripts 
 +
*We used DEseq to normalize data. 
 +
*Data can be normalized using a total read count (TC) normalization. 
  
  

Revision as of 17:11, 13 February 2016

Classwork

Today in class, we shared group findings from January 28, 2016:

  1. Blast the overrepresented sequences
  • Blast groups found mostly mitochondrial or ribosomal genes.
  • Intestine blast group found an amino transferase gene that may be of interest later.
  • Liver blast group found an anti-hemorage gene that may be of interest later.


  1. Attempt to access the list of genes (SRP-0151827) mentioned in the Andrew et al. (2015) study
  • We can blast our sequences against the Andrew et al. (2015) library.
  • We have the potential to download the entire library with instructions on the website, but do not understand how to use the software/programs required to do so.
  • We found a toolkit that allows us to download one sequence at a time.
  • We can blast within a run.


  1. Add numbers to label proteins of "unknown function" in our reads
  • Dylan and Dustin made a file that removed duplicate names from our runs.
  • Dr. Campbell and Dr. Heyer used their file and got gene mapping results!


  1. Normalize relative abundance of transcripts
  • We used DEseq to normalize data.
  • Data can be normalized using a total read count (TC) normalization.





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