Hacker News Reader

Comment by deepsun | Hacker News Reader

Well, DNA is kind of Big Data. And everyone who worked with Big Data knows that there will always be all kinds of inconsistencies and errors.

Personally, I was always skeptical that all non-sex human cells share the same DNA, it's just statistically unbelievable that billions of cells each having billions of DNA pairs would have then equal. I expected something like 1% of cells to have mutations.

Now they say that it's 100% for neurons. Exact 100% number is also pretty sketchy from statistical standpoint.

View on HN

Nobody ever said that all cells share 100% of DNA in the sense you're implying. It's obvious that DNA undergoes dynamic processes, some of which will result in lasting differences. The accumulation of errors is the basic mechanism for cancer, which has been recognised for decades.

But it was previously thought that such differences were detrimental to function (and health). There were some mechanisms for modifying cells' DNA, collectively known as "epigenetics", but these were reversible, at least in principle.

This adds another dimension of complexity, which biology already had plenty of. My favourite is the double- or triple-coding DNA: because DNA is read in triplets, there are three possible reading frames. Some organisms have evolved DNA that produces entirely different, but independently useful proteins on two or even all three reading frames of the same DNA. Talk about efficiency...

Do you have any links for the last paragraph? I know that there can be two gene encoded in reverse in bacteria but have no knowledge of any frame-shifted translations?

About the second paragraph: well, it was not really thought that differences are always detrimental to health, and there is quite a number of variant prioritization tools out there that try to find those variants that are causal compared to all the silent/no-effect mutations (mostly for comparing humans but also somatic).

Look at it from the other end - if there are on average a 1000 difference between two neurons, and a difference can be encapsulated by a single bit you'd have 2^1000 variants - you'd expect to have to look at 2^500 neurons to find a duplicate. And a difference is probably more than one bit.

Now they say that it's 100% for neurons. Exact 100% number is also pretty sketchy from statistical standpoint.

What class of problem is searching for duplicates or uniqueness among a set of billions of items? If it is a tractable problem, what is the most effective algorithm?

Reply on news.ycombinator.com