Splicing defect detection software tools | Whole-genome sequencing data analysis
In silico tools have been developed to predict variants that may have an impact on pre-mRNA splicing. The major limitation of the application of these tools to basic research and clinical practice is the difficulty in interpreting the output. Most tools only predict potential splice sites given a DNA sequence without measuring splicing signal changes caused by a variant.
Predicts which sequences have exonic splicing enhancer (ESE) activity by statistical analysis of exon-intron and splice site composition. When large data sets of human gene sequences were used, RESCUE-ESE identified 10 predicted ESE motifs. Representatives of all 10 motifs were found to display enhancer activity in vivo, whereas point mutants of these sequences exhibited sharply reduced activity. The motifs identified enable prediction of the splicing phenotypes of exonic mutations in human genes.
A web application for 5′ and 3′ splice site prediction. CRYP-SKIP takes up one or more mutated alleles, each consisting of one exon and flanking intronic sequences, and provides a list of important predictor variables and their values, the overall probability of activating cryptic splice vs exon skipping, and the location and intrinsic strength of predicted cryptic splice sites in the input sequence. These results will facilitate phenotypic prediction of splicing mutations and provide further insights into splicing enhancer and silencer elements and their relative importance for splice-site selection in vivo.
Predicts how likely distant mutations around annotated splice sites were to disrupt splicing. Spliceman takes a set of DNA sequences with point mutations and returns a ranked list to predict the effects of point mutations on pre-mRNA splicing. The current implementation included the analyses of 11 genomes: human, chimp, rhesus, mouse, rat, dog, cat, chicken, guinea pig, frog and zebrafish.
A web server for predicting putative splicing factor binding sites in genomic data. SFmap implements the COS(WR) algorithm, which computes similarity scores for a given regulatory motif based on information derived from its sequence environment and its evolutionary conservation. SFmap searches within a given sequence for significant hits of binding motifs that are either stored in the database or defined by the user.
Allows for the identification of putative exonic splicing enhancers (ESEs) and one of its most useful applications is the correct interpretation of the effects of disease-associated point mutations or polymorphisms. The development and refinement of reliable prediction tools for auxiliary splicing elements will have important implications for our ability to accurately identify the exon/intron structures of genes and predict their expression profile, to correctly interpret the effects of point mutations and/or polymorphisms, and to assess phenotypic risk.
Implements Bayesian models for splice site prediction. The predictions are implicitly based on the three variables of (i) degree of matching to the splice site consensus, (ii) local compositional contrast, and (iii) assessment of 3-base periodicity in coding regions.
A service producing neural network predictions of splice sites in human, C. elegans and A. thaliana DNA. The prediction output for both server and mail server consist of the prediction for both direct (+) and complementary (-) strand. The output lists the predictions for donor and acceptor sites in the submitted sequence, as well as branchpoint predictions (for A. thaliana only).
A tool for the detection of exonic variants that modulate splicing. SKIPPY allows users to input a set of exonic variants to score them for a number of features (such as changes in splicing regulatory elements) that have been shown to be predictive of known genome variations that cause exon skipping or activation of ectopic splice sites. In this way, variants can be either prioritized for further splicing-based functional analysis or the results can be used as further genomic evidence in cases in which the causative variant is already known.
A machine-learning approach for the identification of coding region substitutions that disrupt pre-mRNA splicing. Applying MutPred Splice to human disease-causing exonic mutations suggests that 16% of mutations causing inherited disease and 10 to 14% of somatic mutations in cancer may disrupt pre-mRNA splicing.
Predicts the effects of mutations on splicing signals. HSF can forecast the disruption of the natural splice sites and is able to identify splicing motifs in any human sequence. This software combines more than 10 algorithms based on either position weight matrices (PWM), maximum entropy principle or motif comparison method. The PWM evaluates also the strength of 5' and 3' splice sites and branch points.
Artificial neural networks have been combined with a rule based system to predict intron splice sites in the dicot plant Arabidopsis thaliana. A two step prediction scheme, where a global prediction of the coding potential regulates a cutoff level for a local prediction of splice sites, is refined by rules based on splice site confidence values, prediction scores, coding context and distances between potential splice sites. In this approach, the prediction of splice sites mutually affect each other in a non-local manner. The combined approach drastically reduces the large amount of false positive splice sites normally haunting splice site prediction.
A flexible system for detecting splice sites in the genomic DNA of various eukaryotes. The system has been trained and tested successfully on Plasmodium falciparum (malaria), Arabidopsis thaliana, Human, Drosophila, and rice. Training data sets for Human and Arabidopsis thaliana are included.
Allows user to discover insight in pre-mRNA splicing signals. SplicePort is a data analysis tool for the identification of functional elements. It provides two functions: (i) user can perform accurate splice-site prediction with the flexibility of exploring splice site locations, their score, corresponding sensitivity and false positive rate values and (ii) user can explore the motifs for the requested location in the input sequence and browse the complete collection of identified motifs.
Makes splicing signal sequence and scoring data available to the biologist in an integrated, visual, easily interpretable, and user-friendly format. SROOGLE's input consists of the sequence of an exon and flanking introns. The graphic browser output displays the four core splicing signals with scores based on nine different algorithms and highlights sequences belonging to 13 different groups of splicing-regulatory sequences (SRSs). The interface also offers the ability to examine the effect of point mutations at any given position, as well a range of additional metrics and statistical measures regarding each potential signal.
Analyzes and recognizes 5' untranslated region (UTR) intron splice sites in human pre-mRNA. NetUTR is able to recognize splice sites embedded in the coding parts of pre-mRNA with only a small reduction in predictive power. It is based on local splice site information. Compared to NetGene2 on an entire UTR data set, the tool appears to be 2-3-fold better in terms of correlation coefficient.
Estimates the affinity between the protein and the polypyrimidine tract (PPT). BPP can consider the co-evolution between the protein and the binding sequences. It represents the effects of polypyrimidine tract employing relative frequencies for different nucleotides instead of the most commonly used arbitrary scores. This tool provides an alternative method for branch point prediction for human genome study.
Predicts potential splice sites in genomic DNA. FSPLICE allows users to search for both donor and acceptor sites and to define thresholds for them independently. It also allows to search minor variants of splicing donor site (GC-site).
Provides computational biology resources that are related to the genome/transcriptome of the model plant Physcomitrella patens (Aphanoregma patens). Cosmoss is a web app that offer both the transcriptome representation (including a BLAST and retrieval service) and splice site prediction of Physcomitrella. The moss Physcomitrella patens is an emerging plant model system due to its high rate of homologous recombination, haploidy, simple body plan, physiological properties as well as phylogenetic position.
Predicts splice site of the genus Aspergillus. NetAspGene can be combined with a gene finder to develop better annotation for Aspergillus genes. It will be very helpful for the researchers who are interested only in splice sites and in particular alternative splicing. The result can be used to design probes for custom microarrays, for example with the aim to study alternative splicing. The tool is based on a multiple artificial neural networks method.
Predicts the pathogenic and normal intronic single-nucleotide variants (Int-SNVs) using support vector machine (SVM) modeling. IntSplice is a web server that uses 110 parameters to differentiate pathogenic SNVs in the Human Gene Mutation Database and normal SNVs in the dbSNP database. The software allows users to determine aberrant splicing because of intronic single-nucleotide variants (Int-SNVs) at positions from Int-50 to Int-3 (Int-50:Int-3).