SNEEP
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  • Getting started
  • Examples of how to run SNEEP
  • Optional parameters
  • SNEEP result files
  • References
SNEEP
  • SNEEP: SNP exploration and functional analysis using epigenetic data
  • Edit on GitHub

SNEEP: SNP exploration and functional analysis using epigenetic data

logoSneep
  • Getting started
    • Installation
      • Bioconda package
      • Manual installation
    • Testing your installation
    • Basic usage
      • Minimal example
      • Detailed description of the required input files
  • Examples of how to run SNEEP
    • Optional input parameters
    • Examples of realistic applications
      • Example 1: Consider only TFs expressed in the cell type or tissue of interest
      • Example 2: Consider only SNPs in the open chromatin of the cell type of interest
      • Example 3: Associating regulatory SNPs with their target genes
      • Example 4: Compute a proper random background control and highlight cell type-specific TFs
  • Optional parameters
    • Flag -o: Specify an output folder
    • Flag -n: Number of threads
    • Flag -p: p-value threshold for the TF binding score
    • Flag -b and flag -x: base frequency for TF binding score computation
    • Flag -c: p-value threshold for the absolute maximal differential TF binding score
    • Flag -k: dbSNP database (dbSNPs_sorted.txt.gz)
    • Flag -r and -g: Epigenetic interactions
    • Flag -a: Store D:sub: max values for all considered shifts
    • Flag -f: Include open chromatin data
    • Flag -m: Get all D:sub: max values
    • Flag -t, -d and -e: Active TFs of the cell type of interest
    • Flag -j: Number of sampled background SNP sets
    • Flag -l: Reproducible results for random background analysis
    • Flag -q: TF count
  • SNEEP result files
    • Main result file (result.txt)
    • Info file (info.txt)
    • Results of the random background sampling
  • References
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