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The complete FlowSOM package known from R, now available in Python!
Integrative analysis for scTCR- and scRNA-seq data
Analysis methods for analysing single cell RNA-seq data; particularly with the goal of checking if tentative clusters of cells are significantly different to one another in terms of their gene expr…
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
A flexible pipeline for complete analysis of bacterial genomes
Automated generation of tailored bioinformatics Jupyter Notebooks via a user interface.
An interactive heatmap visualization built using D3.js
scRNAseq analysis notes from Ming Tang
Antique or modern atlas-like depictions of non-linear dimensionality reduction for single cell data
A package for the analysis of Imaging Mass Cytometry data
R based workflow for multiplexed imaging data
Robust Integration of Single-Cell Cytometry Datasets
Differential expression analysis for single-cell RNA-seq data.
A tool for semi-automatic cell type classification
A pixel classification based multiplexed image segmentation pipeline
Collection of Tumor-Infiltrating Lymphocyte Single-Cell Experiments with TCR
A game theoretic approach to explain the output of any machine learning model.
Test data to be used for automated testing with the nf-core pipelines
R package to quantify and remove cell free mRNAs from droplet based scRNA-seq data
CellBender is a software package for eliminating technical artifacts from high-throughput single-cell RNA sequencing (scRNA-seq) data.
Fast visualization tool for large-scale and high dimensional single-cell data
A python package for visualization and analysis of high-throughput flow cytometry data