Datensatz

Zusammenfassung

Unlike many well-established organisms, with large scientific communities, gold standard reference genomes, gene predictions and pre-processed gene expression analyses readily available in public databases, more work is typically necessary to analyze RNA-seq in protists. I will introduce some of the computational tools and procedures my laboratory uses in manipulating and analyzing mRNA- seq and sRNA-seq. We use such data in predicting genes from scratch for newly sequenced genomes. Gene prediction is a good starting point for considering RNA-seq data, because without accurate genes, downstream analyses may be problematic. Plenty of errors exist in automated gene predictions that users are often unaware of. Many of these can be manually corrected upon close scrutiny of RNA-seq read mapping or fixed using custom software. I will show some of the tools and approaches we use for such inspections, and allow you to inspect the data yourself. Following this, I will introduce some simple, but powerful analyses combining RNA-seq read mapping with other useful data sources. Finally, I will discuss limitations of current popular functional analyses based on RNA-seq, particularly those reliant upon gene ontologies.