hello folks,
i am learning R and microarray analysis from scratch using different sites.
today i am doing an exercise from
http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual#R_functions
the section i am at is 2. Affymetrix data analysis.
I understand the syntax given in this section up until:
design <- model.matrix(~ -1+factor(c(1,1,2,2,3,3))) # Creates appropriate
design matrix. Alternatively, such a design matrix can be created in any
spreadsheet program and then imported into R.
i am stuck at this point. i believe the model.matrix is creating a design matrix
that the data will be put in later. the data in the example is:
Name FileName Target
Shoot12h.1 COLD_CONTROL_12H_SHOOT_REP1.cel c12h
Shoot12h.2 COLD_CONTROL_12H_SHOOT_REP2.cel c12h
ColdShoot6h.1 COLD_6H_SHOOT_REP1.cel t6h
ColdShoot6h.2 COLD_6H_SHOOT_REP2.cel t6h
ColdShoot12h.1 COLD_12H_SHOOT_REP1.cel t12h
ColdShoot12h.2 COLD_12H_SHOOT_REP2.cel t12h
Three experimental samples (duplicates of each giving a total of 6 arrays).
now back to where i got stuck:
design <- model.matrix(~ -1+factor(c(1,1,2,2,3,3))) # Creates appropriate
design matrix. Alternatively, such a design matrix can be created in any
spreadsheet program and then imported into R.
what is model.matrix exactly doing?
my real data that i will analyze after figuring this out has 49 arrays
(columns): 3, 6, 9, 12 month samples with 9 replicates each and then 23 month
samples with 13 replicates == total 49.
how should i create an appropriate design matrix?? PLEASE help?
thanks,
daniel
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