Single-cell analysis in Python. Scales to >1M cells.
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Updated
Oct 7, 2024 - Python
Single-cell analysis in Python. Scales to >1M cells.
The COnstraint-Based Reconstruction and Analysis Toolbox. Documentation:
pySCENIC is a lightning-fast python implementation of the SCENIC pipeline (Single-Cell rEgulatory Network Inference and Clustering) which enables biologists to infer transcription factors, gene regulatory networks and cell types from single-cell RNA-seq data.
Annotated data.
An interactive explorer for single-cell transcriptomics data
Fusing Histology and Genomics via Deep Learning - IEEE TMI
starfish: unified pipelines for image-based transcriptomics
R package for analyzing single-cell RNA-seq data
A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.
Revolutionizing DNA analysis and making it accessible to all through innovative ML-powered analysis and interpretive tools.
Single cell perturbation prediction
An ontology of cell types
R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
Cellxgene Gateway allows you to use the Cellxgene Server provided by the Chan Zuckerberg Institute (https://github.com/chanzuckerberg/cellxgene) with multiple datasets.
Hierarchical, iterative clustering for analysis of transcriptomics data in R
HMM-integrated Bayesian approach for detecting CNV and LOH events from single-cell RNA-seq data
MERlin is an extensible analysis pipeline applied to decoding MERFISH data
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