epigen

epigen

🏢 Organization

10 repositories on SrcLog

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10 Repos
716 Stars
43 Forks
716 Watchers

Repositories (10)

MrBiomics epigen/MrBiomics R

MrBiomics: Composable modules and recipes automate bioinformatics for multi-omics analyses

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atacseq_pipeline epigen/atacseq_pipeline Python

Ultimate ATAC-seq Data Processing, Quantification and Annotation Snakemake Workflow and MrBiomics Module.

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enrichment_analysis epigen/enrichment_analysis Python

A Snakemake workflow and MrBiomics module for performing genomic region set and gene set enrichment analyses using LOLA, GREAT, GSEApy, pycisTarget and RcisTarget.

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dea_limma epigen/dea_limma R

A Snakemake workflow and MrBiomics module for performing and visualizing differential analyses of NGS data powered by the R package limma.

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scrnaseq_processing_seurat epigen/scrnaseq_processing_seurat R

A Snakemake workflow and MrBiomics module for processing and visualizing (multimodal) sc/snRNA-seq data generated with 10X Genomics Kits or in the MTX matrix file format powered by the R package Seurat.

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genome_tracks epigen/genome_tracks Python

A Snakemake workflow and MrBiomics module for easy visualization of genome browser tracks of aligned BAM files (e.g., RNA-seq, ATAC-seq, scRNA-seq, ...) powered by the wrapper gtracks for the package pyGenomeTracks, and IGV-reports.

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mixscape_seurat epigen/mixscape_seurat R

A Snakemake workflow and MrBiomics module for performing perturbation analyses of pooled (multimodal) CRISPR screens with sc/snRNA-seq read-out (scCRISPR-seq) powered by the R package Seurat's method Mixscape.

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dea_seurat epigen/dea_seurat R

A Snakemake workflow and MrBiomics module for performing differential expression analyses (DEA) on (multimodal) sc/snRNA-seq data powered by the R package Seurat.

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spilterlize_integrate epigen/spilterlize_integrate R

A Snakemake workflow and MrBiomics module to split, filter, normalize, integrate and select highly variable features of count matrices resulting from next-generation sequencing (NGS) experiments (e.g., RNA-seq, ATAC-seq, ChIP-seq, Methyl-seq, miRNA-seq,...) including confounding factor analysis and diagnostic visualizations.

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crop-seq epigen/crop-seq Python

Data analysis scripts for Datlinger et. al, 2017 (doi:10.1038/nmeth.4177)

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