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).

From: SpliceDetector: a software for detection of alternative splicing events in human and model organisms directly from transcript IDs

 

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