simplified cellranger for long-read data
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Updated
Jun 1, 2024 - Python
simplified cellranger for long-read data
Various utility functions for Seurat single-cell analysis
Mutual Information-based Non-linear Clustering Analysis
R package with collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using R.
NicheNet: predict active ligand-target links between interacting cells
CellContrast: Reconstructing Spatial Relationships in Single-Cell RNA Sequencing Data via Deep Contrastive Learning
Characterize A-to-I RNA editing in bulk and single-cell RNA sequencing experiments
Deep probabilistic analysis of single-cell and spatial omics data
Bayesian MCMC matrix factorization algorithm
Guide and links related to bulk and single-cell RNA-Seq experiments.
Spatial Single Cell Analysis in Python
🐟 🍣 🍱 Highly-accurate & wicked fast transcript-level quantification from RNA-seq reads using selective alignment
Inference of Disease Progressive Level in Single-Cell Data
LIANA+: an all-in-one framework for cell-cell communication
DANCE: a deep learning library and benchmark platform for single-cell analysis
R package to predict sex of single cells and identify Male/Female doublets using machine learning approaches
scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics
Detection of allele-specific subclonal copy number alterations from single-cell transcriptomic data.
Simulation and inference of gene regulatory networks based on transcriptional bursting
single-cell and bulk RNA-seq analyses from counts → pathways → drug candidates.
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