In a change to scheduled programming, days after touching down from my holiday (which needs a post of its own) I moved1 to spend the next few weeks back at the Wellcome Trust Sanger Institute in Cambridgeshire. I interned here previously in 2012 and it’s still like working at a science-orientated Google thanks to the overwhelming amount of work being done and the crippling inferiority complex that comes from being surrounded by internationally renowned scientists. Though at least I’m not acquiring significant mass from free food.
My aim here is two fold and outlined below. Though of course, I’m still on the books back at Aberystwyth and it would be both naughty and cruel of me to leave my newly acquired data cold, alone and untouched until I get back.
(1) Produce a Sequel
My undergraduate dissertation was titled: Application of Machine Learning Techniques to Next Generation Sequencing Quality Control and worked in collaboration with some colleagues from my previous placement at the Sanger Institute2. The project was to build a machine learning framework capable of improving detections of “bad” samples by first characterising what it meant to be a bad sample.
In short, the idea was to repeatedly push a large number of samples (each known to have individually passed or failed some internal quality control mechanism) through some analysis pipeline, holding out a single sample out from the analysis in turn. The difference to a known result would then be calculated and samples would be re-classified as good or bad based on whether the accuracy of a particular run was increase or decreased in their absence.
Ultimately the scope was too large and the tools too fragile to complete the end-goal in the time that I had (though it still achieved 90% and won an award, so one can’t complain too much) but we still have the data and while I am here it would be interesting to try and pick up where we left off. I expect to do battle with the following tasks over the next few days:
Recall in detail what we were doing and figure out how far we got
i.e. Dig out the thesis, draw some diagrams and run
Due in part to the short time that I had to complete this project the first time around — a constraint I still have — I authored a tool named
Goldilocks to “narrow down” my analysis from a whole genome to just a 1Mbp window. It would be worth ensuring the latest version of
Goldilocks (which has long fixed some bugs I would really like to forget) still returns the same results as it did when I was doing my thesis.
Confirm data integrity
The data has been sat around in the way of actual in-progress science for the best part of a year and has possibly been moved or “tidied away”. It would be worth ensuring all the files are actually intact and for the sake of completeness revisit how those files came to be and regenerate them. This will encompass ensuring the
Goldilocks region for each sample was correctly extracted. I recall the samples were made up of two studies and we may have decided not to pursue one of them due to differences in sequencing3. I also recall having some major trouble with needing to re-align the failed samples to a different reference: these samples having failed, were not subjected to all the processing of their QC approved counterparts, which we’ll need to apply ourselves manually, presumably painstakingly.
Prepare data for the pipeline
The nail in the coffin for the first stab at this project was the data preparation:
samtools merge was just woefully slow in handling the scale of data that I had, in particular struggling to merge many thousands of files at once. A significant amount of project time was spent tracking and patching memory leaks and contributing other functionality (more on this in a moment) that left me with little time at the end to actually push the data through the pipeline and get results.
samtools has undergone some rapid improvements since and I suspect this step will no longer pose such a hurdle.
(2) Contribute to
As I briefly alluded, during the course of my undergraduate dissertation I authored several pull requests to a popular open-source bioinformatics toolkit known as
samtools, which was initially created and continues to be maintained right here at the Sanger Institute. In particular, these pull requests improved documentation and patched some memory leaks for
samtools merge and also added naive header parsing for input file metadata to be organised into basic structures for much more efficient iterative access later; significantly improving the time performance of
Header parsing has been a long sought after feature for
samtools but none of the core maintainers had the time to put aside to take a good look at the RFC I had submitted. Now I’m in-house and I put a face to a username, catching the most recent
samtools steering meeting off-guard, I’ve been tasked to try and get this done before I leave at the end of July.
- I live in Cambridge until the end of July, please don’t try and find me in my office.4
- For what is at least the 10th major house move I’ve made since heading out to university. ↩
- As soon as I had my foot in the door I refused to take it away. ↩
- The sequencing was conducted at different depths between the two standalone studies and it was suspected this may introduce some bias I didn’t want to deal with. ↩
- Not that I’m ever in there, anyway. ↩