How many transcripts does it take to reconstruct the splice graph?

Abstract

Alternative splicing has emerged as an important biological process which increases the number of transcripts obtainable from a gene. Given a sample of transcripts, the alternative splicing graph (ASG) can be constructed—a mathematical object minimally explaining these transcripts. Most research has so far been devoted to the reconstruction of ASGs from a sample of transcripts, but little has been done on the confidence we can have in these ASGs providing the full picture of alternative splicing. We address this problem by proposing probabilistic models of transcript generation, under which growth of the inferred ASG is investigated. These models are used in novel methods to test the nature of the collection of real transcripts from which the ASG was derived, which we illustrate on example genes. Statistical comparisons of the proposed models were also performed, showing evidence for variation in the pattern of dependencies between donor and acceptor site