Options¶
epic allows for many flags to denote (optional) output files or to change the execution of epic.
-t, –treatment
One or more ChIP files (bed or bedpe format)
-c, –control
One or more input files (bed or bedpe format)
-o, –outfile
File to write results to. By default sent to stdout.
-l, –log
File to write log messages to. Also written to stderr by default.
-cpu, –number-cores
The number of cores epic should use. Can at most take advantage of 1 core per strand per chromosome (i.e. 46 for humans). Default: 1
-gn, –genome
Which genome to analyze. By default hg19.
-k, –keep-duplicates
Keep reads mapping to the same position on the same strand within a library. The default is to remove all but the first duplicate (this is done once per file, not for all files collectively.)
-w, –window-size
Size of the windows (bins) used to scan the genome. This is also the smallest possible enriched region you can get. Default 200.
-g, –gaps-allowed
How many non-enriched windows in a row can be part of the same enriched region. If the number of gaps between two enriched windows is higher than this number, they are considered separate regions. Default: 3
-fs, –fragment-size
(Only used for single-end files) Size of the sequenced fragment. The center of the fragment will be used to calculate which window a read ended up in. So reads are shifted by fragment-size/2. Default 150.
-fdr, –false-discovery-rate-cutoff
Remove all regions with an FDR below cutoff. Note: this also affects which windows are considered enriched in the optional matrix output and which regions are included in the optional bed output.
-egf, –effective-genome-fraction
Use a different effective genome fraction than the one included in epic. Or include an egf for custom genomes that are not a part of epic. Should be a number between 0 and 1. Autoinferred by sampled read-length and genome by default.
-cs, –chromsizes
Set the chromosome lengths yourself in a file with two columns: chromosome names and sizes. Useful to analyze custom genomes, assemblies or simulated data. Only chromosomes included in the file will be analyzed.
-sm, –store-matrix
The path in which to store a gzipped matrix of read counts per window. One column for each ChIP and Input file.
-b, –bed
A summary bed file of all regions, for display in the UCSC genome browser or for use in downstream analyses with e.g. bedtools. The score field is log2(#ChIP/#Input) * 100 capped at a 1000.
-bw, –bigwig
The folder in which to store a RPKM-normalized bigwig for each file in the dataset. The bigwig shows how epic sees the data. It shows all bins, not just those in enriched regions.
-i2bw, –individual-log2fc-bigwigs
The folder in which to store a log2FC bigwig for each ChIP bed/bedpe. Each file is divided against a normalized sum of the Input.
-cbw, –chip-bigwig
Store the sum of the RPKM-normalized ChIP-data to a bigwig file.
-ibw, –input-bigwig
Store the sum of the RPKM-normalized Input-data to a bigwig file.
-v, –version
Show version.