This page describes plans of future features to be implemented in JETTA. Comments and suggestions are appreciated (jseok at stanford dot edu).
Single Condition Alternative Splicing Analysis
In many biomedical studies, it is an interesting problem to measure differences in expression for different splicing events in different genes within a single condition. Statistically, this question can be turned into the problem of finding alternative splicing events that have large variations within a condition compared to the technical variations. The gene/exon specific technical variations can be estimated by repeated measurements of a subset of samples from the condition, i.e. technical repeats. There are several statistical tests for the null hypothesis of the equality of two variances. Using one or more of these tests, we can identify alternatively spliced exons that have significantly higher variations between individual samples within the condition than the estimated technical variations. We will develop this idea further and implement it in JETTA.
Once these alternatively spliced exons with high variations are detected, the major functions or categories of these genes can be further investigated with Gene Ontology or other similar Databases. GSEA and Ingenuity also provides statistical tests for enriched functions in a given set of genes.
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