[Bioc-devel] I would like to publish a bioconductor package.

You can solve the package size issue by putting your example data in a
separate "experiment data" package
(http://www.bioconductor.org/packages/release/data/experiment/).

Stephanie

On 2/27/13 3:03 AM, Davide Rambaldi wrote:

Hi all,

I am working on a library called flowFit, the purpose of this library
is to analyze the FACS data coming from proliferation tracking dyes
study.

The library depends on the flowCore and flowViz bioconductor libraries
and use minpack.lm (levenberg-marquadt algorithm) to fit a set of
peaks over the FACS data.

A typical experimental pipeline:

1) Acquire with FACS a sample of unlabelled cells
2) Acquire with FACS a sample of labeled and unstimulated cells (the
Parent Population)
3) Acquire with FACS a sample of labeled and stimulated cells (the
Proliferative Population)

In R we can use the flowCore functions to transform the raw data and
to gate the population of interest. Once we have gated the correct
population, with 2 commands of flowFit you can perform the fitting:

library(flowFit)
parent <- parentFitting(QuahAndParish[[1]], "<FITC-A>")
fitting <- proliferationFitting(QuahAndParish[[2]],  "<FITC-A>",
parent.fitting.cfse at parentPeakPosition,
parent.fitting.cfse at parentPeakSize)

The function can generate also some graphical output with:

plot(fitting.cfse)

To demonstrate the correctness of the fitting I have made some in
silico simulations and a retrospective analysis of the data from the
paper:

"New and improved methods for measuring lymphocyte proliferation in
vitro and in vivo using CFSE-like fluorescent dyes", Benjamin J.C.
Quah ?, Christopher R. Parish, Journal of Immunological Methods (2012)

In this paper, the same population of lymphocytes (proliferation with
the same growth conditions) was stained with 3 different proliferation
tracking dyes: if the fitting algorithm is working as expected, we
expect to estimate the same % of cells for generation in the 3 sample.

Comparing the 3 samples we didn't see any significant difference in
the estimation of the % of cell for generations, suggesting us that
the algorithm is correctly estimating the % of cells / generation.

I have posted a graphical output example with the Quah and Parish data
(pdf) here:

http://dl.dropbox.com/u/40644496/QuahAndPArishOut.pdf

The dataset will be included in the library (in the data subdir).

Actually I am writing the vignette (I am following the guidelines in
http://www.bioconductor.org/developers/package-guidelines/) and fixing
some graphical bugs (like the legend oversized ?).

The package Pass R CMD build and R CMD CHECK (time: 86 seconds) with
no errors on OSX and Linux (I have to find a windows machine somewhere
...), I still have to test with the R-devel version of R.

The library is bigger than expected (4.2 Mb) because the example
datasets (FCS files converted in .Rdata) are big (3.7M) and I don't
know how to solve this issue...

My question is, How I proceed from here?

I would like to publish the library/methods in a paper (Bioinformatics
Journal may be?) and submit the library to Bioconductor, which is the
correct way to proceed?

Thanks

P.S: If I miss (again!) some FAQ please apologize me

-----------------------------------------------------
Davide Rambaldi, PhD.
-----------------------------------------------------
IEO ~ MolMed
[e] davide.rambaldi at ieo.eu
[e] davide.rambaldi at gmail.com