Abstract
While the effects of confounders on gene expression analysis have been extensively studied there is a lack of equivalent analysis and tools for RNA splicing analysis. Here we assess the effect of confounders in two large public RNA-Seq datasets (TARGET, ENCODE), develop a new method, MOCCASIN, to correct the effect of both known and unknown confounders on RNA splicing quantification, and demonstrate MOCCASIN’s effectiveness on both synthetic and real data.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Copyright
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Posted June 17, 2020.
MOCCASIN: A method for correcting for known and unknown confounders in RNA splicing analysis
