This is a wrapper function making use of other lower-level functions in this package. It looks for immunoassay data files in a given folder, processes these files and accumulates results into a single data frame. Optionally, it can create a project report - either in a simple text form, or in LaTeX format.
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batch(path, subfolder = "", kit.file = NULL, analytes = "all", run.options = list(CTS = 20, MFI = "last", CV = 20), model.options = list(model = "L.5", weights = "sqrt", refit = 0.2, use = 1, stvals = "adaptive"), project.options = list(report = "text", template = "short", trace = TRUE), correct.errors = NULL)
Character string. Path to the main project folder. A csv file with kit data should be located in that folder. Also, all subfolders are created in this folder.
Character string. If the csv files with immunoassay data are located in the subfolder of the main folder, provide its name here. Otherwise, leave blank.
Character string. File name of the csv file containing kit information.
Character or numeric. This parameter is passed to
List of 3 elements that provide validation criteria:
A list of 5 elements. Element
A list of 3 elements. Element
A list - an alternative means to introduce corrections to the fit
parameters for a small number of items. In this list, each named element is a list. The
named element's name must be the name of the datafile that is to be corrected. There
must be two elements in each named sub-list:
batch function is the core function of this library. It implements
automation in processing of entire folders of immunoassay data files. The function
first looks for immunoassay files (currently limited to multiplex data files) under
the provided path - it does so intelligently, so it
can distinguish immunoassay run files from other .csv files. Then it creates a list of names
of these files and processes through this list according to provided options.
For each file from the list, this function loads it using
fits the sigmoidal model using
sigfit function with the set of parameters
model.options. Next, it validates the fitted data using the criteria
run.options parameter, and finally, it creates a report as set in
There are two major advantages of using this function, instead of manually processing the
data: it can save substantial amount of time in processing of large number of data files,
while preserving considerable flexibility in setting fit parameters and applying corrections.
The second major advantage is the ability to create reports. Text reports are useful for
obtaining general insight into the data and fitting process, but this function can really
shine in connection with
Sweave LaTeX report templates, that can be elaborate
programs on themselves.
In order to use LaTeX template option, the user must create a minimum of two template
files. These must be named: "my-project-name.run-report.r" - a template for each plate, and
"my-project-name.project-report.r" - a project-wide template incorporating (or not) individual
plate reports. The
"my-project-name" part of the template name must be provided
template= parameter, when
report="latex" option is used. These templates
are "Sweaved" in the process of running this function.
There is one known problem associated with use of the
Sweave function - it's that the
Sweave works in global environment and doesn't "see" the environment within the
batch function it has been called from. To overcome this, the
sets a global variable - a pointer to its environment, named
Objects and data from within
batch function can be then accessed within the
Sweave templates using
For LaTeX template programmers, the list of the accessible objects within
is as follows:
validate - validation function;
immunoassay.coefs (global) - list of all
immunoassay.kits (global) - a
data.frame with kits information;
ppath - full path to the data files;
files - list of valid
N - number of files (
vector of analyte names;
n - number of analytes (
l.run - a
data.frame of class
ima, containing the validated run
fits - a list of fitted
nls models, of length "n".
After all the plates are processed, additional object becomes available:
data.frame being a collection of all results from all plates, for use in the
This function returns a simple data frame that is the collection of results from all processed
files. It does not contain any fit information - if fit information are required, some form
of report must be called.
In addition to the returned
data.frame this function by default creates three global
immunoassay.coefs list - a list of model coefficients for each fitted
run file, and each model type; the
immunoassay.options - a list of model parameters
for all run files; and
immunoassay.environment - a pointer to the environment of the
batch function for use by the
Sweave report templates.
Examples of LaTeX report templates from an example
project are located in
the "templates" directory in the main package folder. See help for the example project for
Michal J. Figurski, PhD firstname.lastname@example.org of the Biomarker Research Laboratory, University of Pennsylvania, Philadelphia, PA.
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## Not run: a <- batch("path-to-my-project", subfolder="Results", kit.file="kit-file-name.csv", analytes=1:2, model.options = list(model="L.5", weights=c("sqrt","1/y"), refit=0.2, use=1, stvals="adaptive"), project.options = list(report="latex", template="my-project-name", trace=FALSE), correct.errors = list(`Plasma Pl072.csv`=list(name="use", value=c(0,1,0,1,0,1,0,1,0,1,0,1,0,1,0,1)))) ## End(Not run)
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