generate_calls_workflow {BgeeCall} | R Documentation |
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
generate_calls_workflow( abundanceMetadata = new("KallistoMetadata"), bgeeMetadata = new("BgeeMetadata"), userMetadata = NULL, userDataFrame = NULL, userFile = NULL )
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') |
paths to the 4 results files (see vignette for more details)
Julien Wollbrett
AbundanceMetadata, KallistoMetadata, BgeeMetadata, UserMetadata
## 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)