combineOutput {appreci8R} | R Documentation

## Combine output of different variant calling tools

### Description

appreci8R combines and filters the output of different variant calling tools according to the 'appreci8'-algorithm. In the 4th analysis step, all normalized and annotated calls of the different variant calling tools are combined. A GRangesObject with all combined calls is returned.

### Usage

    combineOutput(output_folder, caller_names, annotated_calls_g)

### Arguments

`output_folder` | The folder to write the output files into. If an empty string is provided, no files are written out.
`caller_names` | Vector containing the name of the variant calling tools.
`annotated_calls_g` | A GRangesList object. Every list element contains the variant calls of one variant calling tool. Annotate()-output can directly be taken as input. Providing a list with only one list element, i.e. evaluating only one variant calling tool, is possible, but not assumed to be useful. The point of the appreci8-algorithm lies in the combined evaluation and filtration of the output of several variant calling tools.

### Details

The function `combineOutput` performs a combination of the normalized and annotated variant calls from different variant calling tools. The results are sorted according to Chr, Pos, Ref, Alt and SampleID. If two callers - caller1 and caller2 - report the same variant for the same sample, it is only reported once in the output file with a “1” in the column “caller1” and another “1” in the column “caller2”.

### Value

A GRanges object is returned containing all combined calls. Reported metadata columns are: SampleID, Ref, Alt, Location, c. (position of variant on cDNA level), p. (position of variant on protein level), AA_ref, AA_alt, Codon_ref, Codon_alt, Consequence, Gene, GeneID, TranscriptID. In addition, one column for every variant calling tool is reported, containing a “1” for every call detected by that tool and “NA” for every call not detected by that tool.

If an output folder is provided, the output is saved as Results_Raw.txt.

### Author(s)

Sarah Sandmann <sarah.sandmann@uni-muenster.de>

### See Also

`appreci8R`, `appreci8Rshiny`, `filterTarget`, `normalize`, `annotate`, `evaluateCovAndBQ`, `determineCharacteristics`, `finalFiltration`

### Examples

    library("GenomicRanges")
    gatk<-GRanges(seqnames = c("4","X"),
                  ranges = IRanges(start = c(106196951,15838366),
                                   end = c(106196951,15838366)),
                  SampleID = c("Sample2","Sample1"),
                  Ref = c("A","C"),
                  Alt = c("G","A"),
                  Location = c("coding,coding","coding"),
                  c. = c("5284,5347","864"),
                  p. = c("1762,1783","288"),
                  AA_ref = c("I,I","N"),
                  AA_alt = c("V,V","K"),
                  Codon_ref = c("ATA,ATA","AAC"),
                  Codon_alt = c("GTA,GTA","AAA"),
                  Consequence = c("nonsynonymous,nonsynonymous","nonsynonymous"),
                  Gene = c("TET2,TET2","ZRSR2"),
                  GeneID = c("54790,54790","8233"),
                  TranscriptID = c("18308,18309","75467"))
    varscan<-gatk[2,]
    annotated<-GRangesList()
    annotated[[1]]<-gatk
    annotated[[2]]<-varscan

    combined<-combineOutput("", c("GATK","VarScan"), annotated)

[Package appreci8R version 1.4.0 Index]