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DistanceCheckSheet
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Microarray or mass spec?
Average by sample location?
Do PROC MEANS on each patient to verify normalization
Create/verify peak definition file for each dataset (if not provided by investigator)
Peak ID: 1-n
Patient ID
sample location # for patient
spectra # for sample location
Group
Easy Id for investigator (uniform length)
Create/verify patient definition file for each dataset (if not provided by investigator)
Patient ID: 1-n.
Patient name: name that the investigator can use to easily id the patient
number of sample locations
number of spectra
If averaging Create averaged peak definition file (
SasAverageProgramTemplate
)
Peak ID: 1-n
Patient ID
Group
Easy ID for investigator (uniform length)
Create/verify gene/protien definition file
Gene/protien ID: 1-n
name/label given by investigator
Create group definition file.
Show number of patients/sample locations.
If more than one data set, define and name.
Define each grouping for each data set.
Verify with investigator.
Group definiton file.
Number of patients.
Number of sample locations per patient.
Number of spectra.
Number of patients/sample location in each group.
Number of Groupings.
Generate Scores
Mass Spec. (Log 10)
WGA - log
Sam - log
Info - log
TTest - log
Fisher - 0=0, >0 = 1
Wilcoxen - raw
Microarray (Log 2)
WGA - log
Sam - log
Info - log
TTest - log
Create Summery Chart for scores
Distance run
Verify sign function.
Verify distance function.
Distance graph lables for each grouping
Verify train data sizes with group def.
Verify testing data sizes with group def.
Training error checking
Sample detailed distance output 1-2 per grouping.
Verify sign function.
Verify distance function.
Verify grouping.
Verify groups.
General Tips
Sas
Make sure that ttest/fisher/wilcoxen script has the correct number of genes/protients.
Averaging mass spec
Ignore 0 (average only peaks)
logging
Log only peaks > 0, 0s (non peaks) stay 0
--
JeremyRoberts
- 09 Mar 2004
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Topic revision: r7 - 26 Mar 2004,
JoanZhang
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