C++ library for computational cytometry

License

cytolib provides a c++ library for interacting with cytometry data.

reading FCS into efficient disk-backed and memory-backed data structures
representation of gated cytometry data.
core library backing the R packages flowCore, flowWorkspace, CytoML, and others that provide a high level R language interface.

Reporting Bugs or Issues

Use the issue template in github when creating a new issue.
Follow the instructions in the template (do your background reading).
Search and verify that the issue hasn’t already been addressed.
Check the Bioconductor support site.
Make sure your flow packages are up to date.
THEN if your issue persists, file a bug report.

Otherwise, we may close your issue without responding.

Installation cytolib as a R package

The cytolib package can be installed from Github

    remotes::install_github("RGLab/cytolib")

R packages wishing to use the libraries in cytolib need to:

add cytolib to LinkingTo field in the DESCRIPTION file so the compiler knows where to find the headers when the user package is complied e.g.

LinkingTo: cytolib

See CytoML package for the example of using cytolib.

Installation as a C++ standalone library

System requirement

cmake
g++ (>=4.9) or clang++(>= 7.0.1)
libblas, liblapack, ZLIB, boost c++ library
protobuf c++ library (>= 3.10)

Installation

# enter your project directory
$ cd cytolib

# it is always a good idea to not pollute the source with build files
# so create a new build directory
$ mkdir build
$ cd build

# run cmake to configure the package for your system
$ cmake ..

# to link against the protobuf that is installed at custom location
# e.g. `cmake -DCMAKE_PREFIX_PATH=</path/to/protobuf>`

# to select different compiler other than the default
# e.g. `cmake -DCMAKE_CXX_COMPILER=clang++` 

#To install the library to custom directory, use `-DCMAKE_INSTALL_PREFIX` option
# e.g. `cmake -DCMAKE_INSTALL_PREFIX=/usr/local` 
   
$ make

#to install the package
$ make install