praneet1988/ELeFHAnt
Ensemble Learning for Harmonization and Annotation of Single Cells (ELeFHAnt) provides an easy to use R package for users to annotate clusters of single cells, harmonize labels across single cell datasets to generate a unified atlas and infer relationship among celltypes between two datasets. It uses an ensemble of three machine learning classifiers 1) RF 2) SVM and 3) LR
This tool helps single-cell biologists and researchers analyze single-cell RNA sequencing data. It takes in processed single-cell datasets, typically from R's Seurat package, and outputs annotated cell types, harmonized labels across different datasets, or inferred relationships between cell types. This is ideal for scientists working with single-cell data who need to standardize and interpret their findings.
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Use this if you need to accurately identify cell types in your single-cell data, combine annotations from multiple datasets, or understand how cell populations relate to each other across different experiments or species.
Not ideal if you are looking for a general-purpose machine learning library or if your primary data format is not compatible with Seurat objects.
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Language
R
License
GPL-3.0
Category
Last pushed
Jul 18, 2022
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