diff --git a/README_template.md b/README_template.md index ad82cd7..efbd77e 100644 --- a/README_template.md +++ b/README_template.md @@ -63,7 +63,8 @@ Here are some tips for the usage of this workflow: Detailed specifications can be found here [./config/README.md](./config/README.md) # 📖 Examples ---- COMING SOON --- +For complete working examples, including data and configuration, check out how the following [MR.PARETO Recipes](https://github.com/epigen/mr.pareto/?tab=readme-ov-file#-recipes) use this module +- ... # 🔗 Links - [GitHub Repository](https://github.com/user/module/) @@ -72,16 +73,21 @@ Detailed specifications can be found here [./config/README.md](./config/README.m - [Snakemake Workflow Catalog Entry](https://snakemake.github.io/snakemake-workflow-catalog?usage=user/module) # 📚 Resources -- Recommended [MR.PARETO](https://github.com/epigen/mr.pareto) modules for up-/downstream analyses: - - ... -- ... +- Recommended compatible [MR.PARETO Modules](https://github.com/epigen/mr.pareto/#-modules) for up-/downstream analyses: + - [Unsupervised Analysis](https://github.com/epigen/unsupervised_analysis) to understand and visualize similarities and variations between cells/samples, including dimensionality reduction and cluster analysis. Useful for all tabular data including single-cell and bulk sequencing data. + - [Split, Filter, Normalize and Integrate Sequencing Data](https://github.com/epigen/spilterlize_integrate/) after count quantification. + - [Differential Analysis with limma](https://github.com/epigen/dea_limma) to identify and visualize statistically significantly different features (e.g., genes or genomic regions) between sample groups. + - [Enrichment Analysis](https://github.com/epigen/enrichment_analysis) for biomedical interpretation of (differential) analysis results using prior knowledge. + - [Genome Browser Track Visualization](https://github.com/epigen/genome_tracks/) for quality control and visual inspection/analysis of genomic regions/genes of interest or top hits. + - [ATAC-seq Processing](https://github.com/epigen/atacseq_pipeline) to quantify chromatin accessibility. + - [scRNA-seq Data Processing & Visualization](https://github.com/epigen/scrnaseq_processing_seurat) for processing (multimodal) single-cell transcriptome data. + - [Differential Analysis using Seurat](https://github.com/epigen/dea_seurat) to identify and visualize statistically significantly different features (e.g., genes or proteins) between groups. + - [Perturbation Analysis using Mixscape from Seurat](https://github.com/epigen/mixscape_seurat) to identify perturbed cells from pooled (multimodal) CRISPR screens with sc/snRNA-seq read-out (scCRISPR-seq). # 📑 Publications The following publications successfully used this module for their analyses. - -``` -... -``` +- [FirstAuthors et al. (202X) Journal Name - Paper Title.](https://doi.org/10.XXX/XXXX) +- ... # ⭐ Star History