| affycompTable {affycomp} | R Documentation |
These functions take as an argument the output of the assessment functions.
affycompTable(...,Table=NULL,assessment.list=NULL,method.names=NULL) tableAll(...,assessment.list=NULL,method.names=NULL) tableDilution(l, method.names=NULL) tableFC(l, method.names=NULL) tableFC2(l, method.names=NULL) tableSignal(l, method.names=NULL) tableLS(l, method.names=NULL) tableSpikeInSD(l, method.names=NULL) tableMA2(l, method.names=NULL) tableOverallSNR(...,assessment.list=NULL,method.names=NULL,ngenes=12626) tableRanks(...,assessment.list=NULL,method.names=NULL,ngenes=12626,rank=TRUE)
... |
lists produced by the assessment functions |
Table |
If |
assessment.list |
Alternatively, one can also send a list of lists produced by |
method.names |
A character vector with the names of the epxression measure methodology. |
l |
list of assessments. |
rank |
if |
ngenes |
when computing ranks, out of how many genes should we do it? |
Read the vignette for more details on what the entries of the table
are. affycompTable has a few entries per graph. tableAll
has more entries. Once an
assessment is used this function knows what to do. You can call any of
the assessment functions described in assessSpikeIn,
assessDilution, assessSD,
assessLS, assessMA2, and assessSpikeInSD.
Note tableRanks and tableOverallSNR work on the results
from assessSpikeIn2.
A matrix. One column per each method and one row for each comparison. tableOverallSNR is an exception. Where rows represnt methods.
Rafael A. Irizarry
library(affycompData) data(rma.assessment) ##this was produced with affycomp.assess data(mas5.assessment) ##this one too tmp <- affycompTable(mas5.assessment,rma.assessment) format(tmp,digit=2)