Description Usage Arguments Value Objects from the Class Slots Methods Note Author(s) See Also Examples
The RPPASetSummary class contains the summary information derived from an RPPASet object.
1 2 3 4 5 6 7 8 9 10 | RPPASetSummary(rppaset,
onlynormqcgood=ran.prefitqc(rppaset),
monitor=NULL)
is.RPPASetSummary(x)
## S4 method for signature 'RPPASetSummary'
write.summary(object,
path,
prefix="supercurve",
monitor=NULL,
...)
|
rppaset |
object of class |
onlynormqcgood |
logical scalar. If |
monitor |
object of class |
x |
object of class |
object |
object of class |
path |
character string specifying the path from the current directory to the directory containing the files to be processed |
prefix |
character string used as a prefix on files generated by
the |
... |
extra arguments for generic routines |
The RPPASetSummary
generator returns an object of class
RPPASetSummary
.
The is.RPPASetSummary
method returns TRUE
if its
argument is an object of class RPPASetSummary
.
The write.summary
method invisibly returns NULL
.
Although objects of the class can (in theory) be created by a direct call
to new, the only realistic method is to use the
RPPASetSummary
generator function.
raw
:numeric matrix of raw concentrations
ss
:numeric matrix of R^2 statistical values
norm
:numeric matrix of normalized concentrations
probs
:numeric vector of goodness of fit probabilities,
or NULL
(if pre-fit QC analysis was not requested)
completed
:logical matrix specifying stage completion for each slide
design
:object of class RPPADesign
, common to all
the slides
onlynormqcgood
:logical scalar specifying if raw concentrations were filtered according to their pre-fit quality control scores prior to normalization
version
:character string containing the version of this package used to construct the object
signature(object = "RPPASetSummary")
:
Generates three CSV files: one for the raw concentrations, one
for the R^2 statistics, and one for the normalized concentrations;
a fourth file containing the goodness of fit probabilities may be present
if pre-fit QC analysis was requested. Additionally, a TSV file
detailing completion of each stage of processing for each slide is
produced.
The three CSV files may be reordered (to match that of the original input) when written to disk.
P. Roebuck proebuck@mdanderson.org
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ## Not run:
parentdir <- file.path("C:", "MyData")
txtdir <- file.path(parentdir, "txt") # quantification files
outdir <- file.path(parentdir, "results") # output files
designparams <- RPPADesignParams(grouping="blockSample",
center=FALSE,
aliasfile="layoutInfo.tsv",
designfile="slidedesign.tsv")
fitparams <- RPPAFitParams(measure="Mean.Net",
method="nlrob",
model="cobs",
ignoreNegative=FALSE,
warnLevel=-1,
verbose=FALSE)
normparams <- RPPANormalizationParams(method="vs")
rppaset <- RPPASet(txtdir,
designparams,
fitparams,
normparams=normparams)
## If you REALLY want to do this manually. It will be invoked
## automatically if you invoke write.summary(rppaset) instead...
write.summary(summary(rppaset),
path=outdir,
graphs=FALSE)
## End(Not run)
|
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