The worst part is, I'm not sure which is a more rational desire. Is my my privacy concern undue paranoia?
[1]https://customercare.23andme.com/hc/en-us/articles/202907890...
[2]http://venturebeat.com/2013/09/20/how-to-use-23andme-without...
It's true the writer works for Abine (and she discloses that fact) but it's not relevant. Your comment (unintentionally) makes it sound like Abine is selling an intermediary privacy mailbox for receiving 23andMe data and that's not the case. Copying her steps requires zero interaction with Abine.
>Using your work address for a shipping/billing address is not "hacking [your] way around" anything.
She was using a fake name in combination with a work address which can be an adequate hack for many people if they are not under active FBI surveillance. If the work address has a thousand employees, that might be anonymous "enough". That's probably better anonymity than combining a fake name with your relative's (parent's/sibling's) address.
If one needs more anonymity than the fake name + work address, he/she would have to get way more creative. Possibly get on Silk Road 3.0 to buy a counterfeit government driver's license with an alias -- and use that ID to rent a USPS mailbox for $50. Also maybe get a wig and mustache to avoid face recognition from USPS cameras on the premises. Etc,
And are there genes responsible for it?
On a more serious note, I remember hearing about microchips the size of USB sticks that were supposed to sequence a DNA in hours costing "only" few grands back then couple of years ago. I'm surprised they didn't yet flood the market considering the privacy concerns when it comes to services like 23andMe.
Sure, those services do more just sequencing, but for those who would just like to check for a few hereditary deseases running in their family while sticking to their tinfoil hat that would be a bargain. In my case, though, my body is so tough that I'm afraid if my DNA is revealed it may be used for making a clone army one day.
Isn't it a software/data science problem? And if so, what makes if difficult? Computational complexity or the availability of reference data, or both?
What makes it difficult is several things: the genome itself has many repetitive regions whose lengths are greater than 100 characters. If your sequencing technology produces reads less than 100 characters, you don't have enough information to place those reads within their proper location in the genome.
Next: There are regions that aren't exact duplicates of each other, but are very similar. If you have a 100 character read, and you know it probably contains errors (a necessary consequence of the sequencing technology), it can be hard to assign it precisely to a single region, as the read will match numerous regions equally well. A huge amount of effort is currently put into mapping these reads to the most appropriate location.
Next, because of the high cost of doing the assembly properly, heuristics are used. Often, the heuristics will be based on greedy algorithms, that try to tile overlapping reads to extend the reads into longer segments. However, due to the read error rate, you might accidentally tile two unrelated reads; this wil prevent you from finding the true, optimal solution. To correct for this ambiguity, you typically have to sample a large combinatorial set of possible solutions to find the best ranking one. This is a major area of research.
Mapping reads to reference data is often done (instead of wholesale assembly) but it suffers from the same problems. The reference is highly biased, it was based on a small number of individuals; when you try to map reads from an individual who is genetically distinct from the reference nindividual, there will be large regions that don't map (for example, I believe the reference was a European-American, if you try to map African genomes to that reference, you'll find there are entire regions missing from one that are in the other.
I don't know a lot of CS, but there is probably a term for taking a bunch of reads and mapping them in a way that maximizes the probability of the mapped reads representing the true solution (IE what is actually in the person's genome). Most people come up with heuristics that (IMHO) have serious deficiencies. When I ran Exacycle at Google we used it to do a "real" assembly (full n2 comparison of all read pairs) and we found it was far more accurate than previously assembled genomes. Subsequent to that, Gene Myers (who designed shotgun assemblers) used these reults to find a heuristic that produced assemblies that were nearly as good but at a much lower cost. I'm personally still skeptical.
If sequencers produced 10KB reads with 0.01% error rate, I'd be happy.
It took exacycle 404,000 CPU-hours to do the full n2 comparison (it's an embarassingly parallel problem), but since Exacycle supplied over 600,000 CPU-hours per hour, it took less than one hour to compute. However, that wasn't "scalable" if you wanted to do full de novo assembly on every human (2.8e15 CPU hours) so Myers came up with a heuristic.
From the NLP side of the data munching isle, it sounds like a lot more complicated variations on language processing problems.
Comparing reads to each other is like approximate string matching (or fuzzy matching) we use to account for spelling errors in words, but genome chunks are longer and you don't have dictionaries to check against.
And finding the best arrangement of those reads is akin to language modeling where we assign probabilities to word sequences which later can be used to predict the most likely sequence. In case of genomes, though, with so little data, no standard "words", and the error rates in reads, it's like trying to put back a shredded book of in illiterate author only having few other books of illiterate authors as reference.
it applies the chomsky hierarchy to sequence analysis, there is in fact a ton of interesting literature around graphical models like HMMs, see https://www.amazon.com/Biological-Sequence-Analysis-Probabil... for more details.
Its error rate is too high to be important; the technology is overhyped.
But at some point I think it will be irrelevant because 1,2,3 Generations will triangulate me anyway
Fun reads on reddit genealogy
I want to learn everything my own genome can teach me, but have complete control over which parts of that knowledge I share.
They do that now. That's the whole point of asking for your family medical history.
I could see the day where they offer a discount if you disclose your data just like car insurers offer a discount if you opt-in to tracking.
There are, however, certain gaps in the law. For example, I believe life insurance is not currently covered.
For reference on how unlikely - https://www.congress.gov/bill/110th-congress/house-bill/493/...
04/25/2007 Passed/agreed to in House: On motion to suspend the rules and pass the bill, as amended Agreed to by the Yeas and Nays: (2/3 required): 420 - 3 (Roll no. 261).(text: CR H4083-4094)
04/24/2008 Passed/agreed to in Senate: Passed Senate with an amendment by Yea-Nay Vote. 95 - 0. Record Vote Number: 113.
05/01/2008 Resolving differences -- House actions: On motion that the House agree to the Senate amendment Agreed to by the Yeas and Nays: 414 - 1 (Roll no. 234).(text as House agreed to Senate amendment: CR H2961-2972)
05/19/2008 Presented to President.
05/21/2008 Signed by President.
[The one Nay in the House was Ron Paul].
To the world, I think that having a large dataset helps to improve the quality of studies such as the one being discussed. There's great utility in having a "hold-out set" for verification.
The OP presumably perceives some similar benefits, hence the sense of being "conflicted". Whether the benefits are real is a valid, although separate question than whether the privacy concerns are justified.
Probably. Getting a DNA sample from you would be trivial if someone really wanted it. You throw off genetic material all the time.
At worst, having it already archived on a service lowers the barrier slightly.
You're not protecting yourself against being specifically targeted, you're protecting yourself against getting erroneously caught in a dragnet.
While it is true that anyone could collect your shed cells to analyze, collecting personal artefacts requires some degree of prior specific interest in you sufficient to justify the costs of the collection and analysis - this is a barrier. When your data is uploaded into an easily-searchable database, this barrier is lowered, allowing those with access to trawl the DB for any members matching certain criteria. You should also keep in mind that all of these private databases are open to subpoena by various governmental jurisdictions. If you are familiar with the Birthday Problem and the various common abuses of Bayesian reasoning, you can imagine how this could pose a problem even for law-abiding citizens (and their relatives, remember). Additionally, it should be noted that regulations against adverse use of publicly-stored genetic information (e.g. by insurance companies) are by no means universal.
Aggregated SNP data is very useful for researchers. But the utility of these commercial SNP products for the customer - beyond satisfying personal curiosity - is often overstated. If you are in the fortunate position of having access to a reasonably adequate family medical history and regular physical examinations, you will receive little marginal medical benefit from these services. Many of the phenotypes that customers spend the most time discussing on various fora can be reconstructed with reasonable accuracy from a pedigree, and the predictive power of these assays for many polygenic traits is fairly low at present. If you are interested in a few particular traits (like caffeine or drug metabolism) I would suggest ordering a kit for just those traits at first, and also playing around with data available on the 1000 Genomes website (www.1000genomes.org). This can be a bit more expensive, but it allows you to establish your comfort level with DNA data before exposing you to any privacy concerns. Of course, if you are interested in conducting personal research on your own SNP chip data and are already familiar with the data format and all of the associated statistical caveats, 23 and Me provides a good product at a reasonable price.
Yes.