Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
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Updated
Mar 11, 2023
Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
NicheNet: predict active ligand-target links between interacting cells
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
Spatial alignment of single cell transcriptomic data.
Training and evaluating a variational autoencoder for pan-cancer gene expression data
Deep learning for gene expression inference
Python3 binding to mRMR Feature Selection algorithm (currently not maintained)
Building classifiers using cancer transcriptomes across 33 different cancer-types
R package to access DoRothEA's regulons
Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.
BASiCS: Bayesian Analysis of Single-Cell Sequencing Data. This is an unstable experimental version. Please see http://bioconductor.org/packages/BASiCS/ for the official release version
integrated RNA-seq Analysis Pipeline
Enjoy your transcriptomic data and analysis responsibly - like sipping a cocktail
A repository with exploration into using transformers to predict DNA
Repository for the R package EPIC, to Estimate the Proportion of Immune and Cancer cells from bulk gene expression data.
Data and code related to the paper "ADAGE-Based Integration of Publicly Available Pseudomonas aeruginosa..." Jie Tan, et al · mSystems · 2016
Fast visualization tool for large-scale and high dimensional single-cell data
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