Rapid transformations for cytometry data
Project description
Cytotransfrom
Description
Cytotransform is a python package for transforming flow cytometry data. It implements the following transformations according to the GatingML 2.0 definitions (https://flowcyt.sourceforge.net/gating/latest.pdf):
- Parametrized logarithmic transformation
- Parametrized inverse hyperbolic sine transformation (asinh)
- Logicle transformation
- Hyperlog transformation
Each transformation is implemented as a Transform
class with a transform
method that takes a numpy array as input
and returns the transformed array. The Transform
class also has a transform_inverse
method that takes a numpy array
as input and returns the inverse transformed array. Each implementation includes validation of the input parameters. The
transform classes support multiprocessing out of the box and if n_jobs
is set to more than 0, then the input data will
be split into n
batches depending on the number of cores available and each batch will be transformed in parallel.
If n_jobs
is set to -1, then all available cores will be used. If n_jobs
is set to 0, then no multiprocessing will
be used.
Cytotransform is thanks to the fantastic community of scientists and developers in the single cell and flow cytometry data analysis ecosystem. It implements the FastLogicle C++ library for logicle transformations originally implemented by Wayne A Moore and David R Parks (see https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4761345/). Code was inspired by the great work by Scott White (https://github.com/whitews/FlowKit) and Brian Teague (https://github.com/cytoflow).
Installation
Cytotransform can be installed from PyPi using pip:
pip install cytotransform
Usage
The transform
and inverse_transform
methods take a numpy array or Pandas DataFrame as input and return a numpy the
transformed array/dataframe.
Parametrized logarithmic transformation
from cytotransform import ParametrizedLogTransform
transformer = ParametrizedLogTransform(m=4.5, t=262144, n_jobs=-1)
transformed_data = transformer.transform(data)
data = transformer.inverse_transform(transformed_data)
Parametrized inverse hyperbolic sine transformation (asinh)
from cytotransform import AsinhTransform
transformer = AsinhTransform(m=4.5, t=262144, a=0.0, n_jobs=-1)
transformed_data = transformer.transform(data)
data = transformer.inverse_transform(transformed_data)
Logicle transformation
from cytotransform import LogicleTransform
transformer = LogicleTransform(t=262144, w=0.5, m=4.5, a=0.0, n_jobs=-1)
transformed_data = transformer.transform(data)
data = transformer.inverse_transform(transformed_data)
Hyperlog transformation
from cytotransform import HyperlogTransform
transformer = HyperlogTransform(t=262144, w=0.5, m=4.5, a=0.0, n_jobs=-1)
transformed_data = transformer.transform(data)
data = transformer.inverse_transform(transformed_data)
License
Cytotransform is licensed under the MIT license, is free to use, and comes with no warranty whatsoever.
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