Command: call

Call peaks in a qBED file

usage: blockify call [-h] -i INPUT [--prior PRIOR | --p0 P0]
                     [--method {OP,PELT}] [-r REGIONS] -bg BACKGROUND
                     [--intermediate INTERMEDIATE]
                     (-a ALPHA | -p PVALUECUTOFF) [--correction CORRECTION]
                     [-d DISTANCE] [--min MIN] [--max MAX] [-t | -s]
                     [-c PSEUDOCOUNT] [--measure {enrichment,depletion}]

Named Arguments

-i, --input

Input file


Output file (BED format); default: stdout


Explicit prior on the number of blocks (not recommended for general use)


Empirical prior based on a specified false-positive rate; must be between 0 and 1 (default: 0.05)


Possible choices: OP, PELT

Segment using the optimal partitioning (OP) or pruned exact linear time (PELT) algorithm (default: “PELT”)

-r, --regions

Regions over which to normalize event counts; should be supplied as a BED file. If not provided, the input file will be segmented using Bayesian blocks.

-bg, --background

Background qBED file


Intermediate file to write verbose output (CSV format)

-a, --alpha

Alpha for multiple hypothesis correction (must be between 0 and 1)

-p, --pValueCutoff

p-value cutoff (NOTE: This is a straight cutoff and will not take into account multiple hypothesis correction!)


If alpha provided, need to specificity method of multiple hypothesis correction. See statsmodels.stats.multitest for a complete list of choices (default: “bonferroni”)

-d, --distance

Merge features closer than this distance (bp)


Report peaks larger than this cutoff (bp)


Report peaks smaller than this cutoff (bp)

-t, --tight

Shrink peak boundaries to overlap data points

-s, --summit

Return peak summits

-c, --pseudocount

Pseudocount for background regions (default: 1)


Possible choices: enrichment, depletion

Perform a one-tailed test for either enrichment or depletion relative to the background file (default: “enrichment”)