Alternative splicing results in a single gene coding for multiple protein isoforms, so this task can only be invoked from transcript level data. The algorithm is is based on ANOVA to detect genes with multiple transcripts showing expression changes differently in different biology groups, e.g. a gene has two transcripts: A and B, transcript A is showing up-regulation in the treated group comparing to the control group, while B is showing down regulation in treated group.

## Alt-splicing ANOVA dialog

The alt-splicing dialog is very similar to ANOVA dialog, since the analysis is based on the ANOVA model specified. To setup an ANOVA model, first chose factors from the available sample attributes. The factors can be categorical or numeric attribute(s). Click on a **check box** to select and click **Add factors** button to add a factor to the model (Figure 1).

- Transcript ID effect: not all transcripts of a gene are expressed at the same level, so transcript ID is added to the model to account for transcript-to.transcript differences.
- Interaction of transcript ID with alt-splicing factor: that effect is used to estimate whether different transcripts have different expression among the levels of the same factor.

Suppose there is an experiment designed to detect transcripts showing differential expression in two tissue groups: liver vs muscle. The alt-splicing ANOVA dialog allows you to specify the ANOVA model that in this analysis is the *Tissue*. The alt-splicing factor is chosen from the ANOVA factor(s), so the alt-splicing factor is also *Tissue* (Figure 1).

The alt-splicing range will limit analysis to genes possessing the number of transcripts in the specified range. Lowering the maximum number of transcripts will increase the speed of analysis.

**Next**to setup the comparisons (Figure 2). The levels (i.e. subgroups) of the alt-splicing factor will be displayed in the left panel; click to select a level name and move it to one of the panels on the right. The fold change calculation on the comparison will use the group in the top panel as the numerator, and the group in the bottom panel as the denominator. Click on

**Add comparison**button to add a comparison to the comparisons table.

## ANOVA advanced options

Click on the *Configure* to customize Advanced options (Figure 3).

*Low-expression feature*and

*Multiple test correction*sections are the same as the matching GSA advanced option, so see GSA advanced options discussion.

*Report option*

*User only reliable estimation results:*There are situations when a model estimation procedure does not fail outright, but still encounters some difficulties. In this case, it can even generate p-value and fold change on the comparisons, but they are not reliable, i.e. they can be misleading. Therefore, the default is set to*Yes*.*Data has been log transformed with base*: showing the current scale of the input data on this task.

## Alt-splicing ANOVA report

For this analysis, only genes with more than one transcript will be included in the calculation. The report format is the same as ANOVA report, each row represent a transcript, and besides statistics information on the specified comparisons, there is also alt-splicing information at the right end of the table. That information is represented by the p-value of interaction of transcript ID with alt-splicing factor. Note that the transcripts of the same gene should have the same p-value. Small p-value indicates significant alt-splicing event, hence the table is sorted based on that p-value by default (Figure 4).

To visualize the difference, click on the **Browse to location** icon () (Figure 5). The 3rd exon is differentially expressed between NM_005888 and NM_002635. Muscle primarily expresses NM_005888 while liver primarily uses NM_002635.

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