Abstract

The Sequence Read Archive contains millions of accessions. Large-scale projects like GTEx, ICGC and TOPmed are major contributors, with still larger projects on the horizon. These archives are potential gold mines for researchers but they are not organized for everyday use by scientists. The situation resembles the early days of the World Wide Web, before search engines made the web easy to use. I will describe our methods and software for making making large public RNA sequencing datasets easy to use. I describe our multi-layered design, with one layer for scalable and uniform analysis (Rail-RNA), another for forming easy-to-use summarized (recount3), and a third for indexing the summaries and making them queryable (Snaptron & snapcount). I will then describe collaborations where these tools were applied to (a) evaluate hypotheses about prevalence or specificity of splicing patterns, (b) characterize completeness of the gene annotations, (c) reveal cell-type-specific splicing patterns, and (d) design novel model systems and gene therapies. This is joint work with Leonardo Collado Torres, Andrew Jaffe, Abhinav Nellore, Chris Wilks, Jonathan Ling, Luigi Marchionni, Seth Blackshaw, Jeff Leek, Kasper Hansen and others.