sc12-RPPASetSummary-class: Class "RPPASetSummary"

Description Usage Arguments Value Objects from the Class Slots Methods Note Author(s) See Also Examples

Description

The RPPASetSummary class contains the summary information derived from an RPPASet object.

Usage

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RPPASetSummary(rppaset,
               onlynormqcgood=ran.prefitqc(rppaset),
               monitor=NULL)
is.RPPASetSummary(x)
## S4 method for signature 'RPPASetSummary'
write.summary(object,
              path,
              prefix="supercurve",
              monitor=NULL,
              ...)

Arguments

rppaset

object of class RPPASet

onlynormqcgood

logical scalar. If TRUE, filters the slides to be normalized according to their pre-fit quality control scores.

monitor

object of class SCProgressMonitor

x

object of class RPPASetSummary

object

object of class RPPASetSummary

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 write.summary method

...

extra arguments for generic routines

Value

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.

Objects from the Class

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.

Slots

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

Methods

write.summary

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.

Note

The three CSV files may be reordered (to match that of the original input) when written to disk.

Author(s)

P. Roebuck proebuck@mdanderson.org

See Also

RPPASet

Examples

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  ## 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)

SuperCurve documentation built on May 2, 2019, 6:14 p.m.