The invention provides an SNV detection
system affecting
RNA splicing. The SNV detection
system comprises the following steps of: step 1), according to locus information and
genome sequence information of an SNP file, extracting upstream and downstream sequences at 100bp and a reverse complementary sequence of the locus before and after
mutation; step 2), using the sequences extracted in step 1) to respectively predict splice loci based on three different methods, that is, a maximum
entropy principle, a Markov model and an
artificial neural network; and step 3), integrating according to a
prediction score result of the three methods, and screening out the SNV having an effect on the
RNA splicing. According to the SNV detection
system affecting the
RNA splicing provided by the invention, changes of the
RNA splicing before and after
mutation are predicted by integrating these three methods and taking SNV data as input, and the SNV affecting the
RNA splicing is acquired, thereby effectively improving the prediction accuracy and providing reference for biological experiments and clinical researches.