predictSpliced: Ranges-based identification of splice junctions and exons
In SGSeq: Splice event prediction and quantification from RNA-seq data

Description Usage Arguments Value Author(s)

Ranges-based identification of splice junctions and exons.

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predictSpliced(frag_exonic, frag_intron, min_junction_count, psi, beta, gamma,
  min_anchor, include_counts, retain_coverage, junctions_only, max_complexity,
  sample_name, seqlevel, strand)

`frag_exonic`	`IRangesList` with exonic regions from alignments
`frag_intron`	`IRangesList` with introns implied by spliced alignments
`min_junction_count`	Minimum fragment count required for a splice junction to be included. If specified, argument `alpha` is ignored.
`psi`	Minimum splice frequency required for a splice junction to be included
`beta`	Minimum relative coverage required for an internal exon to be included
`gamma`	Minimum relative coverage required for a terminal exon to be included
`min_anchor`	Integer specifiying minimum anchor length
`include_counts`	Logical indicating whether counts of compatible fragments should be included in metadata column “N”
`retain_coverage`	Logical indicating whether coverage for each exon should be retained as an `RleList` in metadata column “coverage”. This allows filtering of features using more stringent criteria after the initial prediction.
`junctions_only`	Logical indicating whether predictions should be limited to identification of splice junctions only
`max_complexity`	Maximum allowed complexity. If a locus exceeds this threshold, it is skipped, resulting in a warning. Complexity is defined as the maximum number of unique predicted splice junctions overlapping a given position. High complexity regions are often due to spurious read alignments and can slow down processing. To disable this filter, set to `NA`.
`sample_name`	Sample name used in messages
`seqlevel`	`seqlevel` to be processed
`strand`	`strand` to be processed