Fast differential usage, aberrant splicing and expression analysis that scales to large RNA-seq data compendia? Check out our preprint to see how juggling offsets unlocks bulk RNA-seq tools for these applications. Great collaboration with @lievenclement and @elfridedebaere lab!.

RT @mikelove: Also, regarding this new preprint on differential splicing / transcript usage, see @Alex_Segers_'s helpful answer on @jeremy_….

RT @elfridedebaere: saseR dramatically 💫 boosts the performance for aberrant splicing. Work from @Alex_Segers_ & @lievenClement, great coll….

RT @elfridedebaere: 📢 Important & cool paper alert! 📢 saseR is a Scalable Aberrant Splicing and Expression Retrieval framework that outperf….

saseR can further be used for many different applications that model proportions, and allows both short- and long-read sequencing data. It will soon be submitted to Bioconductor.

And last but not least, we also show that using saseR improves power significantly to detect aberrant splicing events.

Then, adapted offsets were used in edgeR and DESeq2 to model differential splicing. Similar power on bulk RNA-seq is obtained, while achieving great scalability.

First, we show that saseR is faster compared to SOTA methods to detect aberrant expression, while retaining similar performance.

RT @lievenClement: Fast differential usage, aberrant splicing and expression analysis that scales to large RNA-seq data compendia? Check @A….