Skip to content

Annotation-free quantification of RNA splicing. Yang I. Li, David A. Knowles, Jack Humphrey, Alvaro N. Barbeira, Scott P. Dickinson, Hae Kyung Im, Jonathan K. Pritchard

License

Notifications You must be signed in to change notification settings

HaReL1/leafcutter

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

leafcutter

Annotation-free quantification of RNA splicing.

Yang I. Li1, David A. Knowles1, Jack Humphrey, Alvaro N. Barbeira, Scott P. Dickinson, Hae Kyung Im, Jonathan K. Pritchard

Leafcutter quantifies RNA splicing variation using short-read RNA-seq data. The core idea is to leverage spliced reads (reads that span an intron) to quantify (differential) intron usage across samples. The advantages of this approach include

  • easy detection of novel introns
  • modeling of more complex splicing events than exonic PSI
  • avoiding the challenge of isoform abundance estimation
  • simple, computationally efficient algorithms scaling to 100s or even 1000s of samples

For details please see our bioRxiv preprint

Full documentation is available at http://davidaknowles.github.io/leafcutter/

If you have usage questions we've setup a Google group here: https://groups.google.com/forum/#!forum/leafcutter-users

We've developed a leafcutter shiny app for visualizing leafcutter results: you can view an example here. This shows leafcutter differential splicing results for a comparison of 10 brain vs. 10 heart samples (5 male, 5 female in each group) from GTEx.

About

Annotation-free quantification of RNA splicing. Yang I. Li, David A. Knowles, Jack Humphrey, Alvaro N. Barbeira, Scott P. Dickinson, Hae Kyung Im, Jonathan K. Pritchard

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • R 40.0%
  • C++ 37.1%
  • Python 14.6%
  • Perl 4.8%
  • Shell 2.0%
  • Stan 1.4%
  • Batchfile 0.1%