Using Bioconductor with High Throughput Assays
Bioconductor includes packages for analysis of diverse areas of high-throughput assays such as flow cytometry, quantitative real-time PCR, mass spectrometry, proteomics and other cell-based data.
The following psuedo-code illustrates a typical R / Bioconductor session. It makes use of the flow cytometry packages to load, transform and visualize the flow data and gate certain populations in the dataset.
The workflow loads the
flowViz packages and its
dependencies. It loads the ITN data with 15 samples, each of which includes,
in addition to FSC and SSC, 5 fluorescence channels: CD3, CD4, CD8, CD69 and
suppressPackageStartupMessages(library(flowCore)) suppressPackageStartupMessages(library(flowStats)) suppressPackageStartupMessages(library(flowViz))
## Load packages library(flowCore) library(flowStats) library(flowViz) # for flow data visualization ## Load data data(ITN) ITN
First, we need to transform all the fluorescence channels. Using a
object can help to keep track of our progress.
## Create a workflow instance and transform data using asinh wf <- workFlow(ITN) asinh <- arcsinhTransform() tl <- transformList(colnames(ITN)[3:7], asinh, transformationId = "asinh") add(wf, tl)
Next we use the
lymphGate function to find the T-cells in the CD3/SSC
## Identify T-cells population lg <- lymphGate(Data(wf[["asinh"]]), channels=c("SSC", "CD3"), preselection="CD4", filterId="TCells", eval=FALSE, scale=2.5) add(wf, lg$n2gate, parent="asinh") print(xyplot(SSC ~ CD3| PatientID, wf[["TCells+"]], par.settings=list(gate=list(col="red", fill="red", alpha=0.3))))
A typical workflow for flow cytometry data analysis in Bioconductor flow packages include data transformation, normalization, filtering, manual gating, semi-automatic gating and automatic clustering if desired. Details can be found in flowWorkFlow.pdf or the vignettes of the flow cytometry packages.
Installation and Use
Follow installation instructions to start using these
packages. To install the
flowCore package and all of its
dependencies, evaluate the commands
## try http:// if https:// URLs are not supported source("https://bioconductor.org/biocLite.R") biocLite("flowCore")
Package installation is required only once per R installation. View a full list of available packages.
To use the
flowCore package, evaluate the command
This instruction is required once in each R session.
Exploring Package Content
Packages have extensive help pages, and include vignettes highlighting common use cases. The help pages and vignettes are available from within R. After loading a package, use syntax like
to obtain an overview of help on the
flowCore package, and the
read.FCS function, and
to view vignettes (providing a more comprehensive introduction to
package functionality) in the
flowCore package. Use
to open a web page containing comprehensive help resources.
Diverse Assays Resources
The following provide a brief overview of packages useful for analysis of high-throughput assays. More comprehensive workflows can be found in documentation (available from package descriptions) and in Bioconductor publications.
These packages use standard FCS files, including infrastructure, utilities, visualization and semi-autogating methods for the analysis of flow cytometry data.
Algorithms for clustering flow cytometry data are found in these packages:
These packages provide data structures and algorithms for cell-based high-throughput screens (HTS).
This package supports the xCELLigence system which contains a series of real-time cell analyzer (RTCA).
High-throughput qPCR Assays
These package provide algorithm for the analysis of cycle threshold (Ct) from quantitative real-time PCR data.
Mass Spectrometry and Proteomics data
These packages provide framework for processing, visualization, and statistical analysis of mass spectral and proteomics data.
Imaging Based Assays
These packages provide infrastructure for image-based phenotyping and automation of other image-related tasks: