generate_calls_workflow {BgeeCall} | R Documentation

## generate present/absent calls

### Description

Main function running the workflow allowing to generate present/absent calls from a file, a data.frame, or objects of the classe UserMetadata (please choose only 1 out of the 3) This workflow is highly tunable by editing default values of the slots of S4 objects. For more information on how to tune the workflow please have a look at the vignette and the documentation of the classes KallistoMetadata, AbundanceMetadata, UserMetadata, and BgeeMetadata

### Usage

    generate_calls_workflow(
      abundanceMetadata = new("KallistoMetadata"),
      bgeeMetadata = new("BgeeMetadata"),
      userMetadata = NULL,
      userDataFrame = NULL,
      userFile = NULL
    )

### Arguments

`abundanceMetadata` | A Reference Class BgeeMetadata object (optional) allowing to tune your gene quantification abundance analyze
`bgeeMetadata` | A Reference Class BgeeMetadata object (optional) allowing to choose the version of reference intergenic sequences
`userMetadata` | A Reference Class UserMetadata object (optional). generate present/allows calls using objects of the UserMetadata class. Can be one object or a list of objects.
`userDataFrame` | a data.frame comtaining all information to generate present/absent calls. Each line of this data.frame will generate calls for one RNA-Seq library. This data.frame must contains 7 columns : - species_id : The ensembl species ID - run_ids : (optional) allows to generate calls for a subpart of all runs of the library. must be a character or a list of characters. - reads_size (optional) the size of the reads of the library (Default = 50) if the reads size is lower than 51 abundance quantification wil be run with a smaller kmer size - rnaseq_lib_path : path to RNA-Seq library directory - transcriptome_path : path to transcriptome file - annotation_path : path to annotation file - working_path : root of the directory where results will be written
`userFile` | path to a tsv file containing 7 columns. these columns are the same than for userDataFrame (see above). a template of this file is available at the root of the package and accessible with the command system.file('userMetadataTemplate.tsv', package = 'BgeeCall')

### Value

paths to the 4 results files (see vignette for more details)

### Author(s)

Julien Wollbrett

### See Also

AbundanceMetadata, KallistoMetadata, BgeeMetadata, UserMetadata

### Examples

    ## Not run:
    # import gene annotation and transcriptome from AnnotationHub
    library(AnnotationHub)
    ah <- AnnotationHub()
    ah_resources <- query(ah, c('Ensembl', 'Caenorhabditis elegans', '84'))
    annotation_object <- ah_resources[['AH50789']]
    transcriptome_object <- rtracklayer::import.2bit(ah_resources[['AH50453']])

    # instanciate BgeeCall object
    # add annotation and transcriptome in the user_BgeeCall object
    # it is possible to import them using an S4 object (GRanges, DNAStringSet)
    # or a file (gtf, fasta) with methods setAnnotationFromFile() and
    # setTranscriptomeFromFile()
    user_BgeeCall <- setAnnotationFromObject(user_BgeeCall,
                                             annotation_object,
                                             'WBcel235_84')
    user_BgeeCall <- setTranscriptomeFromObject(user_BgeeCall,
                                              transcriptome_object,
                                              'WBcel235')
    # provide path to the directory of your RNA-Seq library
    user_BgeeCall <- setRNASeqLibPath(user_BgeeCall,
                     system.file('extdata', 'SRX099901_subset',
                     package = 'BgeeCall'))

    # run the full BgeeCall workflow
    calls_output <- generate_calls_workflow(
                 userMetadata = user_BgeeCall)

    ## End(Not run)

[Package BgeeCall version 1.3.1 Index]