A tutorial overview of
flowPloidy is available on
This vignette is provided with the package, so once you have
installed you can access it from with R (see below).
flowPloidy is available in Bioconductor.
To install it, you need to install the
bioconductor R package (more
details on the Bioconductor site ):
## try http:// if https:// URLs are not supported if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install()
Once that's installed, you can install
flowPloidy using the Bioconductor
BiocManager::install("flowPloidy") BiocManager::install("flowPloidyData") # (optional) data for the examples
This should pull in all the package dependencies for
which you can load the package with the normal function
As of June 2018, I have added a new analysis method. This is aimed at assessing endopolyploidy, where a single sample may have four or more peaks. The intent is to compare the number of cells in each peak, rather than to determine a ratio relative to a co-chopped standard.
This new code will be incorporated into Bioconductor for the next release. If you'd like to try it now, you can install it directly from the GitHub repository as follows:
## Install Bioconductor tools first: if (!requireNamespace("BiocManager", quietly=TRUE)) install.packages("BiocManager") BiocManager::install() ## Install flowCore from Bioconductor: BiocManager::install("flowCore") ## Install devtools so you can directly access GitHub install.packages(devtools) library(devtools) ## Install flowPloidy: install_github("plantarum/flowPloidy", dependencies = TRUE, build_vignettes = TRUE)
If the last command fails, particularly with complaints about building a
vignette, or reference to Pandoc, try with
build_vignettes = FALSE
Note that I haven't yet updated the documentation to match the new code. To
use the endopolyploidy workflow, you need to use a new argument,
FALSE in your call to
batchFlowHist (NB: use g2, lowercase, not G2, uppercase. The original version of this README was incorrect!). This excludes the g2
peaks from peak fitting, treating each peak as an independent group of
cells. You may also want to increase the
samples argument to match the
number of peaks; however, you can correct this in
that's not critical.
## loading files for endopolyploidy analysis: batch1 <- batchFlowHist(endo_files, channel="FL3.INT.LIN", g2 = FALSE, samples = 5) batch1 <- browseFlowHist(batch1)
flowPloidy to handle up to six peaks (and now potentially an
unlimited number if needed) required reworking a bunch of the existing
code, and as part of this the column headings in the tables produced by
tabulateFlowHist are now different from the previous release.
flowPloidy workflow is documented in the vignette, which you can view
fpVig <- vignette("flowPloidy-overview") fpVig ## open vignette in a browser edit(name = fpVig) ## open vignette source code in a text editor
It is also available online.
For general help using the package, you can post questions on
the Bioconductor Support Site. Use the
flowploidy to ensure your question is brought to my attention.
The development repository for
on Github, and you can file bugs
there using the issues tab. You are also welcome to contribute features
or bug-fixes via pull requests!
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