`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.
run_RCNA(obj, ...)# S3 method for default
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 RCNA_object
run_RCNA(obj, estimate_gc = TRUE, verbose = FALSE, ...)
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.
An `RCNA_object` type created by create_RCNA_object.
Additional arguments (unused).
Character vector containing names of subjects
Character single file path detailing a feature-wise annotation file
Character vector containing the name of each subject's output directory
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.
Numeric value detailing the size of the sliding window used to calculate and detect correct GC-content correction.
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.
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.
Character vector containing the filename of the corrected coverage files.
Character vector containing the filename of GC factor files. Used if and only if `estimate_gc` is set to FALSE.
A logical which determines if GC estimation should be performed. For more information, see correct_gc_bias.
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.
Character vector containing the filename of the input coverage file for NKR estimation. Defaults to `file coverage` if not specified.
Numeric value specifying number of cores to use for analysis. Multiple cores will lead to parallel execution.
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.
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.
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.
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`.
Numeric between 0 and 1 which specifies the lower score cutoff. Defaults to `score.cutoff` if not specified.
Numeric between 0 and 1 which specifies the upper score cutoff. Defaults to `score.cutoff` if not specified.
RCNA_analysis object storing commands and parameters from previous function runs on this object. For more information, see RCNA_analysis.
If set to TRUE will display more detailed error messages.
RCNA_object, RCNA_analysis, correct_gc_bias, run_RCNA, estimate_feature_score
## 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)
system("rm -rf output")
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