seqbias_predict: Predicting sequencing bias
In seqbias: Estimation of per-position bias in high-throughput sequencing data

Description Usage Arguments Details Value Author(s) See Also Examples

Predicts sequencing bias given a fit seqbias model

1	seqbias.predict(sb, I)

`sb`	a seqbias object
`I`	a GRanges object

Once a seqbias model is fit with 'seqbias.fit', the sequencing bias of any region in the reference sequence can be predicted using this function. Given the coordinates of a region, this function produces a vector of the same length as the sequence. Each position 'i' is given a sequence score 'v_i'.

A simple procedure is then to normalize read counts given the sequencing bias. The read count of (i.e. the number of reads beginning on) position 'i', denoted by 'x_i', can be normalized by computing 'x_i/v_i', giving an estimate of abundance that is more accurate in expectation.

A list of numeric vectors are returned, one for each genomic interval in I. The vectors are of equal length to the interval given, and the predicted sequencing bias is given for each position.

Daniel Jones dcjones@cs.washington.edu

seqbias.fit

  reads_fn <- system.file( "extra/example.bam", package = "seqbias" )
  ref_fn <- system.file( "extra/example.fa", package = "seqbias" )

  sb <- seqbias.fit( ref_fn, reads_fn )

  I <- GRanges( c('seq1'), IRanges( c(1), c(5000) ), strand = c('-') )

  bias <- seqbias.predict( sb, I )