Difference between revisions of "February 2, 2016"
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'''Today in class, we shared group findings from [[January 28, 2016]]:''' | '''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. | |
| − | + | 2. 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. | |
| − | + | 3. 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! | |
| − | + | 4.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 17:13, 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.
2. 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.
3. 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!
4.Normalize relative abundance of transcripts
- We used DEseq to normalize data.
- Data can be normalized using a total read count (TC) normalization.
