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#==============================================================================#
# fitQC.R: quality control functions:
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
# fitQC: plm, rlm (medianpolish)
# fitPLM: PLM-type "probe-level model" quality control
# fitRLM: RMA-type "median polish" quality control
# rmaPLM: RMA-type "median polish" quality control
#==============================================================================#
"fitQC" <-
function(xps.data,
## --
filename = character(),
filedir = getwd(),
tmpdir = "",
update = FALSE,
## --
bgcorrect.method = "rma",
bgcorrect.select = "none",
bgcorrect.option = "pmonly:epanechnikov",
bgcorrect.params = c(16384),
## --
normalize.method = "quantile",
normalize.select = "pmonly",
normalize.option = "transcript:together:none",
normalize.logbase = "0",
normalize.params = c(0.0),
## --
qualify.method = "rlm",
qualify.select = "pmonly",
qualify.qualopt = "all",
qualify.option = "transcript",
qualify.estimator = "huber",
qualify.logbase = "log2",
qualify.params = list(10, 0.01, 1.0),
## --
reference.index = 0,
reference.method = "mean",
reference.params = list(0.0),
## --
exonlevel = "",
xps.scheme = NULL,
add.data = FALSE,
bufsize = 32000,
verbose = TRUE)
{
if (is(xps.data, "DataTreeSet")) {
set <- xpsQualityControl(xps.data,
filename = filename,
filedir = filedir,
tmpdir = tmpdir,
update = update,
bgcorrect.method = bgcorrect.method,
bgcorrect.select = bgcorrect.select,
bgcorrect.option = bgcorrect.option,
bgcorrect.params = bgcorrect.params,
normalize.method = normalize.method,
normalize.select = normalize.select,
normalize.option = normalize.option,
normalize.logbase = normalize.logbase,
normalize.params = normalize.params,
qualify.method = qualify.method,
qualify.select = qualify.select,
qualify.qualopt = qualify.qualopt,
qualify.option = qualify.option,
qualify.estimator = qualify.estimator,
qualify.logbase = qualify.logbase,
qualify.params = qualify.params,
reference.index = reference.index,
reference.method = reference.method,
reference.params = reference.params,
exonlevel = exonlevel,
xps.scheme = xps.scheme,
add.data = add.data,
bufsize = bufsize,
verbose = verbose);
return(set);
} else {
stop(paste(sQuote("xps.data"), "is not a class", sQuote("DataTreeSet")));
}#if
}#fitQC
#------------------------------------------------------------------------------#
#"fitPLM" <-
#function(xps.data,
# filename = character(),
# filedir = getwd(),
# tmpdir = "",
# update = FALSE,
# qualopt = "all",
# option = "transcript",
# exonlevel = "",
# xps.scheme = NULL,
# add.data = FALSE,
# bufsize = 32000,
# verbose = TRUE)
#{
# if (is(xps.data, "DataTreeSet")) {
# set <- fitQC(xps.data,
# filename = filename,
# filedir = filedir,
# tmpdir = tmpdir,
# update = update,
# bgcorrect.method = "rma",
# bgcorrect.select = "none",
# bgcorrect.option = "pmonly:epanechnikov",
# bgcorrect.params = c(16384),
# normalize.method = "quantile",
# normalize.select = "pmonly",
# normalize.option = paste(option, "together:none", sep=":"),
# normalize.logbase = "0",
# normalize.params = c(0.0),
# qualify.method = "plm",
# qualify.select = "pmonly",
# qualify.qualopt = qualopt,
# qualify.option = option,
# qualify.estimator = "huber",
# qualify.logbase = "log2",
# qualify.params = list(10, 0.01, 1.0), #to do!!!
# reference.index = 0,
# reference.method = "mean",
# reference.params = list(0.0),
# exonlevel = exonlevel,
# xps.scheme = xps.scheme,
# add.data = add.data,
# bufsize = bufsize,
# verbose = verbose);
# return(set);
# } else {
# stop(paste(sQuote("xps.data"), "is not a class", sQuote("DataTreeSet")));
# }#if
#}#fitPLM
#------------------------------------------------------------------------------#
"fitRLM" <-
function(xps.data,
filename = character(),
filedir = getwd(),
tmpdir = "",
background = "pmonly",
normalize = TRUE,
qualopt = "all",
option = "transcript",
exonlevel = "",
params = list(16384, 0.0, 1.0, 10, 0.01, 1),
xps.scheme = NULL,
add.data = FALSE,
bufsize = 32000,
verbose = TRUE)
{
## skip normalization/bgrd correction dependent on qualopt
bg.adjust <- "rma";
if (qualopt == "raw") {normalize <- FALSE; bg.adjust <- "none";}
if (qualopt == "adjust") {normalize <- FALSE;}
if (is(xps.data, "DataTreeSet")) {
set <- fitQC(xps.data,
filename = filename,
filedir = filedir,
tmpdir = tmpdir,
update = FALSE,
# bgcorrect.method = "rma",
bgcorrect.method = bg.adjust,
bgcorrect.select = background,
bgcorrect.option = "pmonly:epanechnikov",
bgcorrect.params = unlist(params[1]),
normalize.method = ifelse(normalize, "quantile", "none"),
normalize.select = "pmonly",
normalize.option = paste(option, "together:none", sep=":"),
normalize.logbase = "0",
normalize.params = unlist(params[2:3]),
qualify.method = "rlm",
qualify.select = "pmonly",
qualify.qualopt = qualopt,
qualify.option = option,
qualify.estimator = "huber",
qualify.logbase = "log2",
qualify.params = unlist(params[4:6]),
reference.index = 0,
reference.method = "mean",
reference.params = list(0.0),
exonlevel = exonlevel,
xps.scheme = xps.scheme,
add.data = add.data,
bufsize = bufsize,
verbose = verbose);
return(set);
} else {
stop(paste(sQuote("xps.data"), "is not a class", sQuote("DataTreeSet")));
}#if
}#fitRLM
#------------------------------------------------------------------------------#
"rmaPLM" <-
function(xps.data,
filename = character(),
filedir = getwd(),
tmpdir = "",
background = "pmonly",
normalize = TRUE,
qualopt = "all",
option = "transcript",
exonlevel = "",
params = list(16384, 0.0, 1.0, 10, 0.01, 1),
xps.scheme = NULL,
add.data = FALSE,
bufsize = 32000,
verbose = TRUE)
{
if (is(xps.data, "DataTreeSet")) {
set <- fitRLM(xps.data,
filename = filename,
filedir = filedir,
tmpdir = tmpdir,
background = background,
normalize = normalize,
qualopt = qualopt,
option = option,
exonlevel = exonlevel,
params = params,
xps.scheme = xps.scheme,
add.data = add.data,
bufsize = bufsize,
verbose = verbose);
return(set);
}#if
}#rmaPLM
#------------------------------------------------------------------------------#
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