Single-cell analysis in Python. Scales to >1M cells.
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Updated
Dec 23, 2024 - Python
Single-cell analysis in Python. Scales to >1M cells.
An interactive explorer for single-cell transcriptomics data
A Python implementation of the DESeq2 pipeline for bulk RNA-seq DEA.
Annotated data.
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.
Fusing Histology and Genomics via Deep Learning - IEEE TMI
Single cell perturbation prediction
The COnstraint-Based Reconstruction and Analysis Toolbox. Documentation:
starfish: unified pipelines for image-based transcriptomics
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
Automatic Annotation on Cell Types of Clusters from Single-Cell RNA Sequencing Data
R package for analyzing and interactively exploring large-scale single-cell RNA-seq datasets
Differential expression analysis for single-cell RNA-seq data.
Reference-guided transcript discovery and quantification for long read RNA-Seq data
A list of web-based interactive biological data visualizations.
🐟 🔬🦀 alevin-fry is an efficient and flexible tool for processing single-cell sequencing data, currently focused on single-cell transcriptomics and feature barcoding.
R package for analyzing single-cell RNA-seq data
Python package to perform enrichment analysis from omics data.
Brings bulk and pseudobulk transcriptomics to the tidyverse
Transcript discovery and quantification with long RNA reads (Nanopores and PacBio)
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