convertToOneBasedRanges {ORFik} | R Documentation

## Convert a GRanges Object to 1 width reads

### Description

There are 5 ways of doing this 1. Take 5' ends, reduce away rest (5prime) 2. Take 3' ends, reduce away rest (3prime) 3. Tile to 1-mers and include all (tileAll) 4. Take middle point per GRanges (middle) 5. Get original with metacolumns (None)

### Usage

    convertToOneBasedRanges(
      gr,
      method = "5prime",
      addScoreColumn = FALSE,
      addSizeColumn = FALSE,
      after.softclips = TRUE
    )

### Arguments

`gr` | GRanges, GAlignment Object to reduce
`method` | the method to reduce, see info. (5prime defualt)
`addScoreColumn` | logical (FALSE), if TRUE, add a score column that sums up the hits per unique range This will make each read unique, so that each read is 1 time, and score column gives the number of hits. A useful compression. If addSizeColumn is FALSE, it will not differentiate between reads with same start and stop, but different length.
`addSizeColumn` | logical (FALSE), if TRUE, add a size column that for each read, that gives original width of read. Useful if you need original read lengths. This takes care of soft clips etc.
`after.softclips` | logical (TRUE), TRUE: include softclips in size

### Details

You can also do multiple at a time, then output is GRangesList, where each list group is the operation (5prime is [1], 3prime is [2] etc)

Many other ways to do this have their own functions, like startSites and stopSites etc. To retain information on original width, set addSizeColumn to TRUE. To compress data, 1 GRanges object per unique read, set addScoreColumn to TRUE. This will give you a score column with how many duplicated reads there were in the specified region.

NOTE: Does not support paired end reads for the moment!

### Value

Converted GRanges object

### See Also

Other utils: `bedToGR()`, `fimport()`, `findFa()`, `fread.bed()`, `optimizeReads()`, `readBam()`, `readWig()`

[Package ORFik version 1.6.9 Index]