A toolkit package of batch effects removal
Project description
A toolkit for data integration
Behold, a magnificent toolkit emerges, designed to seamlessly integrate the vast realm of data in the realm of single-cell genomics. Within its hallowed digital confines, this toolkit bestows upon researchers the power to harmoniously merge and analyze the intricate tapestry of cellular information. Crafted with meticulous care, this toolkit embodies the epitome of elegance and efficiency. It serves as a conduit, enabling the synthesis of diverse datasets from single-cell genomics experiments, unlocking new realms of knowledge and understanding. The power of data integration within this toolkit extends beyond mere aggregation. It empowers researchers to unravel the intricate web of cellular interactions, uncovering hidden patterns, identifying novel cell types, and discerning the complex dynamics that govern cellular behavior. Through its refined algorithms and advanced statistical techniques, this toolkit illuminates the path towards deeper insights and discoveries. It refines and enhances the quality of data, mitigating confounding factors and removing noise, thus unveiling the true essence of the cellular landscape. As the sun sets on the horizon of single-cell genomics, this toolkit emerges as a guiding beacon, illuminating the path towards a more comprehensive understanding of cellular complexity. Embrace its power and unlock the secrets hidden within the realm of single-cell genomics.
Dependence
Install
The stereoAlign
python package is available on Pypi and can be installed through
pip install stereoAlign
Import stereoAlign
in python
import stereoAlign
We created the python package called stereoAlign
that uses scanpy
to streamline the integration of single-cell datasets and evaluate the results. The package contains several modules for preprocessing an anndata
object, running integration methods and evaluating the resulting using a number of metrics. Functions for the data integration methods are in stereoAlign.alignment
or for short stereoAlign.alg
and metrics are under stereoAlign.metrics
.
Integration Tools
This repository contains the code for the stereoAlign
package for data integration tools.
This toolkit that is compared include:
Integration Method | Invoke | Describe |
---|---|---|
Harmony | stereoAlign.alg.harmony_alignment |
Harmony wrapper function based on harmony-pytorch https://github.com/lilab-bcb/harmony-pytorch |
Scanorama | stereoAlign.alg.scanorama_alignment |
Scanorama wrapper function based on scanorama https://github.com/brianhie/scanorama |
scGEN | stereoAlign.alg.scgen_alignment |
scGen wrapper function based on scgen https://github.com/theislab/scgen with parametrization taken from the tutorial notebook https://scgen.readthedocs.io/en/stable/tutorials/scgen_batch_removal.html. |
scvi | stereoAlign.alg.scvi_alignment |
scVI wrapper function based on scvi-tools version >=0.16.0 (available through https://docs.scvi-tools.org/en/stable/installation.html) |
MNN | stereoAlign.alg.mnn_alignment |
MNN wrapper function (mnnpy implementation) based on mnnpy package https://github.com/chriscainx/mnnpy |
BBKNN | stereoAlign.alg.bbknn_alignment |
BBKNN wrapper function based on bbknn package https://github.com/Teichlab/bbknn |
Combat | stereoAlign.alg.combat_alignment |
ComBat wrapper function (scanpy implementation) using scanpy implementation of Combat https://scanpy.readthedocs.io/en/stable/generated/scanpy.pp.combat.html |
DESC | stereoAlign.alg.desc_alignment |
DESC wrapper function based on desc package https://github.com/eleozzr/desc |
More methods | Additional methods are being incorporated... |
Metric
Metric Method | Invoke |
---|---|
ARI | stereoAlign.metrics.ari |
Graph connectivity | stereoAlign.metrics.graph_connectivity |
KBET | stereoAlign.metrics.get_kbet |
LISI | stereoAlign.metrics.get_lisi |
Silhouette | stereoAlign.metrics.silhouette |
Disclaimer
This is not an official product.
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