run_sicer: Run Sicer2

Description Usage Arguments Value Examples

View source: R/run_sicer.R

Description

Sicer2 is a spatial clustering approach for the identification of ChIP-enriched regions which was developed for calling broad peaks of histone modifications from ChIP-seq data.

Usage

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run_sicer(
  treatment = NULL,
  control = NULL,
  comparison.names = NULL,
  species = NULL,
  redundancy_threshold = 1,
  window_size = 200,
  fragment_size = 150,
  effective_genome_fraction = 0.74,
  false_discovery_rate = 0.01,
  gap_size = 600,
  e_value = 1000,
  step_score = NULL,
  cpu = NULL,
  significant_reads = FALSE,
  sicer = NULL
)

Arguments

treatment

List of the paths to files containing the treatment files. This can either be the relative or the absolute path of the file. Must be in BED or BAM format.

control

List of the paths to files containing the control files. This can either be the relative or the absolute path of the file. Must be in BED or BAM format. OPTIONAL.

comparison.names

List of the comparisons to be made. OPTIONAL.

species

The species/genome used (ex: hg38).

redundancy_threshold

The number of copies of indentical reads allowed in a library. Default is 1.

window_size

Resolution of SICER. Default value is 200 (bp)

fragment_size

The amount of shift from the beginning of a read to the center of the DNA fragment represented by the read. Default is 150 (bp).

effective_genome_fraction

Effective genome as fraction of the genome size. Default is 0.74.

false_discovery_rate

Remove all islands with an false_discovery_rate below cutoff. Default is 0.01.

gap_size

The minimum length of a "gap" such that neighboring window is an "island." This value must be a multiple of the window size. Default is 600 (bp).

e_value

Requires user input when no control library is provided. Default is 1000.

step_score

Step Score: The minimum number of positive elements in the graining unit to call the unit positive. Used for RECOGNICER algorithm.

cpu

The number of CPU cores SICER program will use when executing multi-processing tasks. Optimal core count is the species' number of chromosomes. Default value is the maximum number of cores avaiable in the system.

significant_reads

SICER produces a BED file of treatment reads filtered by significant islands and WIG file of filtered reads binned into windows

sicer

Path to the Sicer2 program

Value

A list with the Sicer2 commands

Examples

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## Not run: 
 sicer.cmds <- run_sicer(treatment = treatment.list,
                         control = control.list,
                         comparison.names = comp.list,
                         significant_reads = TRUE,
                         sicer = sicer.path
                        )

## End(Not run)

GrahamHamilton/pipelineTools documentation built on June 19, 2021, 1:08 p.m.