run_RCNA {RCNA}R Documentation

run_RCNA: Perform RCNA copy number detection workflow

Description

'run_RCNA' will execute correct_gc_bias, estimate_nkr, and estimate_feature_score in that specific order. For more information, see each of those functions' individual documentation.

'run_RCNA' will execute correct_gc_bias, estimate_nkr, and estimate_feature_score in that specific order. For more information, see each of those functions' individual documentation, or create_RCNA_object.

'run_RCNA' will execute correct_gc_bias, estimate_nkr, and estimate_feature_score in that specific order. For more information, see each of those functions' individual documentation.

Usage

run_RCNA(obj, ...)

## Default S3 method:
run_RCNA(
  obj = NULL,
  sample.names,
  ano.file,
  out.dir = tempdir(),
  gcParams = NULL,
  win.size = 75,
  gc.step = 0.01,
  file.raw.coverage = NULL,
  file.corrected.coverage = NULL,
  file.gc.factor = NULL,
  estimate_gc = TRUE,
  nkrParams,
  file.nkr.coverage = NULL,
  ncpu = 1,
  nkr = 0.9,
  x.norm = NULL,
  scoreParams,
  score.cutoff = 0.5,
  low.score.cutoff = NULL,
  high.score.cutoff = NULL,
  commands = c(),
  verbose = FALSE,
  ...
)

## S3 method for class 'RCNA_object'
run_RCNA(obj, estimate_gc = TRUE, verbose = FALSE, ...)

Arguments

obj

An 'RCNA_object' type created by create_RCNA_object.

...

Additional arguments (unused).

sample.names

Character vector containing names of subjects

ano.file

Character single file path detailing a feature-wise annotation file

out.dir

Character vector containing the name of each subject's output directory

gcParams

Data Frame storing all run parameters for the correct_gc_bias function. Can be specified by a file path to a CSV file, 'data.frame', or (if not specified) will be generated by other arguments.

win.size

Numeric value detailing the size of the sliding window used to calculate and detect correct GC-content correction.

gc.step

Numeric value detailing the size of each GC-content bin. If providing pre-calculated GC factor file this must match the bins in that file.

file.raw.coverage

Character vector containing the filename of the raw coverage files for GC-content correction. Must be used in combination with 'estimate_gc' set to TRUE.

file.corrected.coverage

Character vector containing the filename of the corrected coverage files.

file.gc.factor

Character vector containing the filename of GC factor files. Used if and only if 'estimate_gc' is set to FALSE.

estimate_gc

A logical which determines if GC estimation should be performed. For more information, see correct_gc_bias.

nkrParams

Data Frame storing all run parameters for the estimate_nkr function. Can be specified by a file path to a CSV file, 'data.frame', or (if not specified) will be generated by other arguments.

file.nkr.coverage

Character vector containing the filename of the input coverage file for NKR estimation. Defaults to 'file coverage' if not specified.

ncpu

Numeric value specifying number of cores to use for analysis. Multiple cores will lead to parallel execution.

nkr

Numeric between 0 and 1 which specifies the coverage quantile that should be considered a "normal" karyotype range for each position. Lowering this value may increase sensitivity but also Type I error.

x.norm

Logical vector with length equal to the length of 'sample.names', denoting whether each subject has to be X-normalized. Subjects with an XX karyotype should be set to TRUE to avoid double-counting the coverage on the X chromosome. Set to FALSE if chrX coverage is already normalized.

scoreParams

Data Frame storing all run parameters for the estimate_feature_score function. Can be specified by a file path to a CSV file, 'data.frame', or (if not specified) will be generated by other arguments.

score.cutoff

Numeric between 0 and 1 which specifies the score filter on the results file. This parameter creates a symmetrical cutoff around 0, filtering all results whose absolute value is less than the specified value. Non-symmetrical cutoffs can be specified using 'low.score.cutoff' and 'high.score.cutoff'.

low.score.cutoff

Numeric between 0 and 1 which specifies the lower score cutoff. Defaults to 'score.cutoff' if not specified.

high.score.cutoff

Numeric between 0 and 1 which specifies the upper score cutoff. Defaults to 'score.cutoff' if not specified.

commands

RCNA_analysis object storing commands and parameters from previous function runs on this object. For more information, see RCNA_analysis.

verbose

If set to TRUE will display more detailed error messages.

Value

A RCNA_object class object that was used during the workflow, with RCNA_analysis objects in the 'commands' slot that describes the run parameters and results of each step in the workflow.

A RCNA_object class object that was used during the workflow, with RCNA_analysis objects in the 'commands' slot that describes the run parameters and results of each step in the workflow. For more details on outputs, see estimate_nkr, correct_gc_bias, and estimate_feature_score.

A RCNA_object class object that was used during the workflow, with RCNA_analysis objects in the 'commands' slot that describes the run parameters and results of each step in the workflow. For more details on outputs, see estimate_nkr, correct_gc_bias, and estimate_feature_score.

See Also

RCNA_object, RCNA_analysis, correct_gc_bias, run_RCNA, estimate_feature_score

Examples

## Run RCNA workflow on example object
# See ?example_obj for more information on example
example_obj@ano.file <- system.file("examples" ,"annotations-example.csv", package = "RCNA")
raw.cov <- system.file("examples", "coverage",
                       paste0(example_obj@sample.names, ".txt.gz"), package = "RCNA")
example_obj@gcParams$file.raw.coverage <- raw.cov
example_obj
# Run RCNA workflow
result_obj <- run_RCNA(example_obj)


[Package RCNA version 1.0 Index]