Running a big RNA-seq project is easy(ish)

Last year we completed our largest ever RNA-seq project: 528 samples of TruSeq mRNA, 60 lanes of HiSeq 2500 SE50, 13 billion reads - and all in 16 weeks. Being able to do such a large project in such a short time and get high quality data from nearly all samples really demonstrates the robustness of RNA-seq. If you're thinking that a project larger than 96 samples might be too much to consider, then come and talk to us (and Bioinformatics) at a Tuesday afternoon experimental design meeting - and we'll convince you it can be a pretty smooth process.

We've been using Illumina's TruSeq mRNA-seq automated on our Agilent Bravo robot and the sequencing was done on HiSeq 2500, although we're currently  moving to HiSeq 4000.

• 528 samples processed on six-plates of RNA-seq
• QC lanes sequenced and analysed
• 60 lanes of SE50bp sequencing in total, 10 lanes per plate
• 12,918,018,345 PF reads for this project (215M reads per lane on average)
• 24M reads per sample on average
• 16 weeks from start to finish

This has been a large and complex project where we had lots of discussions along the way. I think that everyone involved has contributed to the success so far: the research group who asked us to do the project, my lab, and also our Bioinformatics Core. The ability to discuss the experiment at different stages, and to focus on QC issues as they arise really makes using the Cores a great place to do your projects.