As argued by Chiappori and Donni (2009); Vermeulen (2002); and Bargain et al. (2010), the income pooling assumption made in this approach is not exempt from criticisms, and it has been rejected in some empirical studies.
Although neither of the two pooling probability assumptions is truly realistic in a biological sense, the " equal expression" assumption arguably provides the better approximation.
We performed the in silico experiments using two different pooling probability assumptions.
The first assumption, to which we refer as the " equal pooling probability" assumption, has previously been described by Tress and co-workers [ 12].
Under the first assumption to which we refer as the "equal pooling probability" assumption, all in silico generated peptides are equally abundant and therefore have the same probability (1/N) of being pooled, which depends on the size of initial peptide population (N).
The first, " equal pooling probability" assumption, indicated that AS events were under-represented in all experimental peptide sets.
In a previous proteomics study performed on Drosophila data, the same " equal pooling probability" assumption was used for generating peptide samples and determining the number of expected AS events [ 12].
Under the " equal pooling probability" assumption, the number of experimentally confirmed AS events in the Castellana set was 2.2 times smaller than the expected number of events as determined by the in silico experiments (Table 4; Simulations A).
