single-cell_sib_scilifelab_2021
Single Cell Analysis Workshop
An online summer school providing hands-on knowledge on advanced topics in Single Cell Omics analysis
SciLifeLab SIB Summer School for Advanced topics in Single Cell Omics. Site: https://nbisweden.github.io/single-cell_sib_scilifelab_2021/
23 stars
44 watching
12 forks
Language: Jupyter Notebook
last commit: almost 5 years agoLinked from 1 awesome list
Related projects:
| Repository | Description | Stars |
|---|---|---|
| An educational resource offering interactive R, Python, and Seurat labs for analyzing single-cell RNA sequencing data. | 199 | |
| An online course on single-cell transcriptomics using the Seurat pipeline and R | 78 | |
| An online single-cell analysis course with lecture materials, lab exercises, and collaboration tools | 6 | |
| Educational materials and exercises for a course on advanced topics in single-cell transcriptomics | 17 | |
| Provides a comprehensive tutorial and workflow for single-cell RNA-seq analysis | 1,419 | |
| An educational workshop on single-cell RNA-seq analysis using the Seurat R package | 0 | |
| An open-source R package providing tools and methods for analyzing single cell RNA-seq data | 217 | |
| Analyzing single-cell RNA-seq data using R and Bioconductor tools | 76 | |
| Tools and methods for analyzing single-cell RNA sequencing data, including expression normalization and differential gene expression analysis. | 22 | |
| An interactive software tool for analyzing single-cell omics data | 32 | |
| A package for processing and visualizing single-cell RNA-seq data in R, providing an efficient and customizable framework for analyzing complex biological datasets. | 60 | |
| Probabilistic analysis tools for single-cell omics data | 1,270 | |
| An educational resource teaching computational analysis of single-cell RNA-seq data using R and Bioconductor tools | 125 | |
| Analyzes single-cell multi-omics data from various modalities like RNA-seq and ATAC-seq | 16 | |
| Software tool for analyzing single-cell RNA-seq data from brain tumor samples. | 38 |