How I would do a group-buy of methylation analysis.
(N.B. this is “thinking out loud” and not actually a plan I intend to execute)
Methylation is a pretty commonly discussed epigenetic factor related to aging. However it might be the case that this is downstream of other longevity factors.
The mechanism of the sequencer is that it does direct-reads (instead of reading amplified libraries, which destroy methylation unless specifically treated for it), and off the device is a time-series of electrical signals, which are decoded into base calls with a ML model. Unsurprisingly, community members have been building their own base caller models, including ones that are specialized to different tasks.
Why I think this is cool? Mostly because ONT makes a $1k sequencer than can fit in your pocket, and can do well in excess of 1-10Gb reads before needing replacement consumables. This is mostly me daydreaming what I would want to do with it.
Aside: they also have a pretty cool $9k sample prep tool, which would be useful to me since I’m empirically crappy at doing bio experiments, but the real solution would probably just be to have a contract lab do all the steps and just send the data.
How I would do a group-buy of methylation analysis.
(N.B. this is “thinking out loud” and not actually a plan I intend to execute)
Methylation is a pretty commonly discussed epigenetic factor related to aging. However it might be the case that this is downstream of other longevity factors.
I would like to measure my epigenetics—in particular approximate rates/locations of methylation within my genome. This can be used to provide an approximate biological age correlate.
There are different ways to measure methylation, but one I’m pretty excited about that I don’t hear mentioned often enough is the Oxford Nanopore sequencer.
The mechanism of the sequencer is that it does direct-reads (instead of reading amplified libraries, which destroy methylation unless specifically treated for it), and off the device is a time-series of electrical signals, which are decoded into base calls with a ML model. Unsurprisingly, community members have been building their own base caller models, including ones that are specialized to different tasks.
So the community made a bunch of methylation base callers, and they’ve been found to be pretty good.
So anyways the basic plan is this:
Extract a bunch of cells (probably blood but could be other sources)
Extract DNA from cells
Prep the samples
Sequence w/ ONT and get raw data
Use the combined model approach to analyze the targets from this analysis
Why I think this is cool? Mostly because ONT makes a $1k sequencer than can fit in your pocket, and can do well in excess of 1-10Gb reads before needing replacement consumables. This is mostly me daydreaming what I would want to do with it.
Aside: they also have a pretty cool $9k sample prep tool, which would be useful to me since I’m empirically crappy at doing bio experiments, but the real solution would probably just be to have a contract lab do all the steps and just send the data.