Difference between revisions of "Kzebrows Week 11"
From LMU BioDB 2015
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#*dye swaps: green and red dye behave differently in experiments | #*dye swaps: green and red dye behave differently in experiments | ||
#**Figure out how many dye swaps occurred (best is even, but they could have done half and half and swapped it or used technical replicates) | #**Figure out how many dye swaps occurred (best is even, but they could have done half and half and swapped it or used technical replicates) | ||
| − | #*Flow chart | + | #*Flow chart (will go into final paper and presentation!) |
| − | #Sample and data relationships: | + | #Sample and data relationships: Match each chip/filename with a sample. One file should correspond to one chip. ('''look at by next week''') |
#*raw.zip should have the files in it | #*raw.zip should have the files in it | ||
#*sdrf.txt (Sample Data Relationship File) spreadsheet | #*sdrf.txt (Sample Data Relationship File) spreadsheet | ||
#*NOTE: Double-check with Dr. Dahlquist | #*NOTE: Double-check with Dr. Dahlquist | ||
#Create compiled raw data file with ID, sample log 2 fold, sample log size, etc. | #Create compiled raw data file with ID, sample log 2 fold, sample log size, etc. | ||
| + | #Normalization and stats (scaling and centering data, calculating T tests and B-H/Bonferroni corrections). Can consult with Dr. Dahlquist for customized procedure. | ||
| + | #*Goal: do a sanity check and compare to what was actually written in the paper to see if it matches (probably not identical but same magnitude and direction) | ||
| + | #GenMAPP: format data and run through GenMAPP and MAPPFinder (converge here with Coder and QA) | ||
| + | #*Do biological interpretation of the data, analyze, and find out something new because the paper did not have this kind of analysis previously | ||
| + | #*Identify exceptions and feed info back to QA person (a few hundred is ok, just hopefully not more than 10% of genome) | ||
| + | |||
| + | '''Deliverables''': responsible for describing methods, how raw data file was found, etc., data tables, GenMAPP and MAPPFinder analysis and interpretation. Compare or contrast in discussion what was found vs. what coder and QA found. | ||
Revision as of 23:29, 10 November 2015
Guild Meeting 10/11: GenMAPP Users
- Experimental design (for sure do by next week)
- Treatment vs. control
- Biological vs. technical replicates: which one and how many
- Biological replicates: independent samples
- Technical replicates: if at any point sample is split into two and treated differently
- NOTE: should be able to find # chips or microarrays (a combo of the above should add up to this)
- dye swaps: green and red dye behave differently in experiments
- Figure out how many dye swaps occurred (best is even, but they could have done half and half and swapped it or used technical replicates)
- Flow chart (will go into final paper and presentation!)
- Sample and data relationships: Match each chip/filename with a sample. One file should correspond to one chip. (look at by next week)
- raw.zip should have the files in it
- sdrf.txt (Sample Data Relationship File) spreadsheet
- NOTE: Double-check with Dr. Dahlquist
- Create compiled raw data file with ID, sample log 2 fold, sample log size, etc.
- Normalization and stats (scaling and centering data, calculating T tests and B-H/Bonferroni corrections). Can consult with Dr. Dahlquist for customized procedure.
- Goal: do a sanity check and compare to what was actually written in the paper to see if it matches (probably not identical but same magnitude and direction)
- GenMAPP: format data and run through GenMAPP and MAPPFinder (converge here with Coder and QA)
- Do biological interpretation of the data, analyze, and find out something new because the paper did not have this kind of analysis previously
- Identify exceptions and feed info back to QA person (a few hundred is ok, just hopefully not more than 10% of genome)
Deliverables: responsible for describing methods, how raw data file was found, etc., data tables, GenMAPP and MAPPFinder analysis and interpretation. Compare or contrast in discussion what was found vs. what coder and QA found.
