MAPS
Cell type annotator
A machine learning framework for annotating cell types from spatial proteomics data
Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications
49 stars
3 watching
9 forks
Language: Jupyter Notebook
last commit: 11 months ago
Linked from 1 awesome list
cell-annotationmpifmultiplexed-imaging
hallvaaw/awesome-biological-image-analysisRelated projects:
| Repository | Description | Stars |
|---|---|---|
 zjufanlab/scdeepsort | A tool for accurately annotating cell types in single-cell RNA sequencing data using deep learning | 100 |
| zjufanlab/sccatch | Automated tool for annotating cell types from single-cell RNA sequencing data based on marker genes | 219 |
 bayraktarlab/cell2location | An algorithmic framework for resolving cell types in spatial transcriptomics data | 327 |
 schmollerlab/cell_acdc | A Python framework for analyzing and annotating microscopy data | 138 |
 angelolab/ark-analysis | A toolset for analyzing multiplexed imaging data by applying various machine learning and image processing techniques to segment cells, cluster pixels, and perform spatial analysis. | 78 |
 celvoxes/cellama | Automates cell type annotation using large language models and provides extensive customized reports | 144 |
 tanaylab/metacell | An R package that facilitates analysis of single-cell RNA-seq data by identifying homogeneous groups of cells. | 110 |
 mouseland/cellpose | A software framework for cell segmentation in microscopy images with human-in-the-loop capabilities and image restoration | 1,415 |
 apress/matlab-machine-learning | Source code accompanying a textbook on machine learning in MATLAB | 84 |
 teichlab/cellity | A tool for identifying and classifying low-quality cells in single-cell RNA sequencing data using machine learning and statistical methods. | 37 |
 swainasish/spatialprompt | A software tool for analyzing spatial transcriptomics data by separating cell types from location information | 12 |
 brainglobe/cellfinder | Automated 3D cell detection tool for large images in microscopy and neuroscience research | 181 |
 vanvalenlab/deepcell-tf | A deep learning library for analyzing biological images at the single-cell level | 431 |
 sentinal4d/cellshape | Analyzes 3D cell shape features using deep learning for cancer research | 21 |
 turagalab/decode | An implementation of a deep learning-based tool for single-molecule localization microscopy with high accuracy and speed. | 96 |