Table 1.

An example of comparing Alternative Splicing events abundance before and after treatment. Total number of Exon Skipping events for each transcript before the treatment equals with Unique transcript number of reads before treatment multiply by ES event number of that transcript in control sample and similarly, total number of ES events for each transcript after the treatment equals with Unique transcript number of reads after treatment multiply by ES event number of that transcript in treated sample. Then a Chi-square goodness of fit test evaluates the significance of the difference in total number of ES events on the whole experiment level before and after the treatment. The number of final events may be adjusted on the whole experiment level with a non significant p-value (part a), or show a significant total alteration of AS events (part b).

	transcripts	Fold Change	Exon Skipping Event count	Before treatment (Control)		After treatment (Treatment)
				Unique reads count	All transcripts ES event	Unique reads count	All transcripts ES event
(a)	Transcript 1 (Upregulated)	2	1	40	40	80	80
	Transcript 2 (Downregulated)	0.5	2	40	80	20	40
	Total ES event				120		120
	Chi square goodness of fit (120,120): 1 → p-value: Not significant
(b)	Transcript 1 (Upregulated)	2	2	40	80	80	160
	Transcript 2 (Downregulated)	0.5	1	40	40	20	20
	Total ES event				120		180
	Chi square goodness of fit (120,180): 0.0005 → p-value: Significant