Splice-Alternative Profile Predictor (SpliceAPP) is an interactive web server for the prediction of RNA splicing in human, and a searchable database of collected splicing variants carried out by our prediction tool.

Prediction SpliceAPP predicts RNA splicing perturbed by human disease-assoicated near-exon intronic variants.
Browse To avoid waiting time, searching and browsing the predicted entries in the database is recommended, which are also available for download.
Intructions Information on job submission can be accessed.
Evaluation For further information on the performance of the predictivon tool.
Contact Any queries about the website or services? Let us know.

Approximately 10-30% of disease-associated genetic variants affect splicing. Splicing variants may generate deleteriously altered gene product which are determined as potential therapeutic targets. However, experimental diagnosis for splicing variants is time-consuming and reliable computational prediction tools have not been established, especially for the near-exon intronic splice region. The major challenge lies in the redundant and ill-defined branch sites and other splicing motifs therein.

From the 11% variants significantly altering 3’ss splicing, we identified two distinct splicing altering mechanisms, novel splice site competition and branch site dysfunction, whereas the splicing altering mechanism of the 5’ intronic variants is mainly the splice site destruction. Statistical learning combined with these molecular features allows precise prediction for altered splicing from an intronic end variant. Based on the training data, the predictive models accept variants -78 to -4 of the 3’ end and -3 to +30 of the 5’ end of the intron.

citation: Chiang, HL., Chen, YT., Su, JY. et al. Mechanism and modeling of human disease-associated near-exon intronic variants that perturb RNA splicing. Nat Struct Mol Biol 29, 1043–1055 (2022). https://doi.org/10.1038/s41594-022-00844-1

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