作者: Halit Ongen , Emmanouil T. Dermitzakis
DOI: 10.1016/J.AJHG.2015.09.004
关键词: Computational biology 、 Human genome 、 Biology 、 Alternative splicing 、 Gene expression profiling 、 Genetics 、 Population 、 RNA splicing 、 Genome 、 Quantitative trait locus 、 Replicate
摘要: With the advent of RNA-sequencing technology, we can detect different types alternative splicing and determine how DNA variation regulates splicing. However, given short read lengths used in most population-based experiments, quantifying transcripts accurately remains a challenge. Here present method, Altrans, for discovery quantitative trait loci (asQTLs). To assess performance compared it to Cufflinks MISO simulations asQTL discovery. Simulations show that presence unannotated transcripts, Altrans performs better quantifications than MISO. We have applied Geuvadis dataset, which comprises samples from European African populations, discovered (FDR = 1%) 1,427 166 asQTLs with 1,737 304 Europeans Africans, respectively. that, by discovering set smaller subset replicating these remaining larger Europeans, both methods achieve similar replication levels (95% methods). find many Altrans-specific asQTLs, replicate high degree (93%). This is mainly due junctions absent annotations hence not tested Cufflinks. The are significantly enriched biochemically active regions genome, functional marks, variants regions, highlighting their biological relevance. an approach more direct assessment other complementary transcript quantification methods.