View source: R/fusion_standardization.R
fusion_standardization | R Documentation |
Various fusion callers have different formats that make aggregating and filtering data difficult. By standardizing fusion callers output we capture the required columns which we use for downstream analysis
fusion_standardization( fusion_calls, caller = c("STARFUSION", "ARRIBA", "CUSTOM"), tumorID = "tumorID", input_json_file = "No file exists" )
fusion_calls |
A dataframe from star fusion or arriba (more callers to be added) |
caller |
string options STARFUSION/ARRIBA |
tumorID |
string or character vector of same length as fusion_calls |
input_json_file |
(optional) json format config file to provide input and output columns headers required for CUSTOM type and not required for other callers |
Standardized fusion calls ready for filtering
Krutika S Gaonkar, Saksham Phul (phuls@chop.edu)
# read in arriba fusion file fusionfileArriba <- read_arriba_calls( system.file("extdata", "arriba_example.tsv", package = "annoFuseData") ) # read in starfusion file fusionfileStarFusion <- read_starfusion_calls( system.file("extdata", "starfusion_example.tsv", package = "annoFuseData") ) formattedArriba <- fusion_standardization(fusionfileArriba, caller = "ARRIBA", tumorID = "tumorID" ) formattedStarFusion <- fusion_standardization(fusionfileStarFusion, caller = "STARFUSION", tumorID = "tumorID" ) # read in CUSTOM type file fusionfileCustom <- data.frame( Sample = c("BS_WDC88K6G", "BS_6J9HGSSB", "BS_K62F9BCS"), FusionName = c("KIAA1549--BRAF", "TFG--GPR128", "SPECC1L--NTRK2"), Gene1A = c("KIAA1549", "TFG", "SPECC1L"), Gene1B = c("BRAF", "GPR128", "NTRK2"), Gene2A = c("", "", ""), Gene2B = c("", "", ""), Fusion_Type = c("", "", ""), annots = c( "[Cosmic,ChimerPub,ChimerSeq,chimerdb_pubmed,ChimerKB,INTRACHROMOSOMAL[chr7:1.74Mb]]", "[ChimerPub,GTEx,ChimerKB,Greger_Normal,ChimerSeq]", "[INTERCHROMOSOMAL[chr22--chr9]]") ) formattedCUSTOM <- fusion_standardization(fusionfileCustom, caller = "CUSTOM", tumorID = "All", input_json_file = system.file("extdata", "config", package = "annoFuseData") ) # format of the input_json_file ("Input_header" : "Output_header") # { # "CUSTOM":{ # "Sample": "Sample_output", # "FusionName": "FusionName_output", # "Gene1A": "Gene1A_output", # "Gene1B": "Gene1B_output", # "Gene2A": "Gene2A_output", # "Gene2B": "Gene2B_output", # "Fusion_Type":"Fusion_Type_output", # "annots":"annots_output" # } # }
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