Deep probabilistic analysis of single-cell and spatial omics data
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Updated
Jun 9, 2024 - Python
Deep probabilistic analysis of single-cell and spatial omics data
muon is a multimodal omics Python framework
Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).
Single cell analysis in the browser
Toolkit for highly memory efficient analysis of single-cell RNA-Seq, scATAC-Seq and CITE-Seq data. Analyze atlas scale datasets with millions of cells on laptop.
Finding surprising needles (=genes) in haystacks (=single cell transcriptome data).
ADTnorm normalizes the cell surface protein measurement of CITE-seq data, facilitating across batches and across studies data integration.
scPerturb: A resource and a python/R tool for single-cell perturbation data
scAR (single-cell Ambient Remover) is a deep learning model for removal of the ambient signals in droplet-based single cell omics
Tools for single-cell feature barcoding analysis
Novel joint clustering method with scRNA-seq and CITE-seq data
Scripts related to bulkRNA-seq as well as single-cell CITE-seq and VDJ-seq data of Gearty et al. (2021)
Code and results from TotalSeqC antibody titration and pipeline benchmarking for CITE-seq experiments
scpca-nf is the Nextflow workflow for processing Single-cell Pediatric Cancer Atlas Portal data
CITE-seq profiling of human PBMCs at baseline and activation conditions
Material for Bioconductor 2023 workshop on interoperation with python
A single-cell demultiplexing pipeline, the sharp (♯)
A framework for simulation of spatially-resolved omics data using python
MultiModal Classifier Hierarchy (MMoCHi)
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