Difference between revisions of "Electronic notebook: sinorhizobium meliloti"
From LMU BioDB 2013
(→Week 12) |
(→Week 13) |
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*Preformed a Pvalue test | *Preformed a Pvalue test | ||
*added a row of N next to the gene ID name in the forGenMAPP tab | *added a row of N next to the gene ID name in the forGenMAPP tab | ||
− | *uploaded | + | *uploaded [[Media:Complete_processed_Data.xls|Processed Data]] |
==week 15== | ==week 15== |
Revision as of 18:00, 5 December 2013
Week 12
- Read the paper on the salinity and sucrose stress on gene expression
- Sorted the raw data into an XML file
- started to compile the raw data
- downloaded all raw data and sorted through the information needed
- used the cys5 and cys3 fold change as well as all the IDs
- Uploaded 300 NaCl compiled data set
Week 13
- I continued to sort the raw data and began to process the data in an xls file
- this was a very repetitive part because it involved a lot of replications for each time set
- finished my compiled raw data and processed raw data, as well as the data ready for GenMAPP
- Made individual LOG fold change ratios for each time point replicate then averaged all of the LOG fold change ratios for each of the time points
- preformed a Tstat test
- Preformed a Pvalue test
- added a row of N next to the gene ID name in the forGenMAPP tab
- uploaded Processed Data
week 15
- I worked on some of the mistakes that I had made in my prior data sets
- removed AVG_LOGFC_ALL row
- added individual Pvalues and TSTAT for each individual replicate of the experiment instead of one Tstat and P value for the whole experiment
- sanity check concluded the number of genes significantly changed at each time point
- T15- 5520
- T30- 7484
- T60- 6711
- T240- 5901
- Removed all of the #DIV/0! from the data that was transferred over to the GenMapp data
- uploaded XLS Version and TXT version, USE THIS
- had to change names of the columns in order to correctly upload to GenMAPP
- system code column was renamed
- Gene ID column was renamed to ID on the Programmers computer to resolve some issues
- it appears that there is something wrong with the actual gene IDs that is not compatible with GenMAPP
- ran the first integration of the data and came up with 5535 errors which is roughly half of the overall genes we loaded.