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Quantifying the impact of mutations on enhancer dynamics

Codebase for manuscript titled: "Quantifying the impact of mutations on enhancer dynamics" by Das and Banerjee et al.

Note

Raw data processing and quality control pipeline of the processed data analyzed in this repo is described here: https://github.com/deeprob/starrseq_reproducibility

Repository guidelines

This repo contains step-by-step guide to the analysis carried out for " ". A description of each sub dir is as follows:

  • 0_quality_control: STARR-seq data quality control scripts.

  • 1_compare_activity_ko_vs_wt: Differential enhancer activity calling scripts.

  • 2_categorize_fragment_on_activity: Defining categories of differentially active enhancers.

  • 3_motif_enrichment_fragment_category: Motif enrichment analysis of various categories of enhancers.

  • 4_ml_classification_fragment_category: Deep Learning models to classify fragments based on their enhancer activity.

  • 5_compare_expression_ko_vs_wt: Differential gene expression scripts.

  • 6_link_da_enhancers_to_de_genes: Mapping enhancers to target genes scripts.

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Codebase for manuscript titled "Quantifying the impact of mutations on enhancer dynamics"

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