If you would have actually read the report, you would have known the attacks are not specifically device or mobile OS bound. They simply say that iOS leaves behind more useable traces.
From paragraph 10:
Much of the targeting outlined in this report involves Pegasus attacks targeting iOS devices. It is important to note that this does not necessarily reflect the relative security of iOS devices compared to Android devices, or other operating systems and phone manufacturers. In Amnesty International’s experience there are significantly more forensic traces accessible to investigators on Apple iOS devices than on stock Android devices, therefore our methodology is focused on the former. As a result, most recent cases of confirmed Pegasus infections have involved iPhones.
You can be traced in many, many ways. From all the websites you visit, the accounts you have, social media posts and pictures, connections with others, camera's outside, your car, your job, whatever more. There's very little true privacy in modern urban life.
Yet, while privacy issues are a point of concern among geneticists when it comes to direct-to-consumer genetic testing, the general points of caution are directed to relational and emotional issues. Many people think little of the relational consequences genetic testing can bear, where family members are implicated often unwillingly. Another point is that people often make up wrong conclusions about their results and see them as some infallible passport of who they are, while the tests are limited in what they actually can tell. Or let's say tests show you have a disposition for increased disease risk. I doubt many give it a really good thought of whether they truly want to know and live with said knowledge for the rest of their lives.
They would need to purify the DNA (remove all other amino acids and membrane proteins etc.) to amplify it and remove any traces of chemicals used for the amplification.
But A) naked DNA will be exposed to the elements/chemicals which could cause damage/denaturation, B) it would look really odd to find batches of pure DNA without any hairs/cells/other proteins.
Maybe some techniques exist to replicate more believable tissue? Honestly not sure as I'm not too well versed on lab-techniques other than sequencing.
That's not what DNA tests do. They do not tell you whether you are factually X% of A and Y% of B, as they do not have the data to make such claims and they do not have DNA of ones' ancestors except through inference.
What they do tell you is that, based on current day large-scale survey data which they use to identify markers, you share certain markers with certain contemporary groups. Especially the percentages they give you should take with a grain of salt as they are approximations to a ground truth (one which nobody fully knows).
I understand that Excel allows for a quick glance, but I'm not sure how R does not offer the same visual cues? Assuming that the data originates from some csv/table structure, Excel requires some GUI clicking and R needs a read.csv() call.
I would say R is a lot more useful for a quick check on whether all columns have one data structure, contain NaN/NA's, are of equal length, etc.
Excel is great, and generally really useful. But not so much in microbiology. Sure, if you have several dozen genes/proteins with some quantitative values and some conditional formatting to visually distinct certain properties, it's fine.
But in microbiology you usually works with very large datasets that undergo a lot of calculations through a lengthy pipeline. Larger sets and more intense ML approaches even need HPC's. Inserting Excel into this pipeline would be catastrophic.
As a bioinformatician I'm not too fond of this shift. Software should be sculpted around our needs, not the other way around. It's basically submitting to the fact that we've stubbed our toes hundreds of times to the exact same rock and never learned.
But then again, I use Excel rarely, usually only at the very end of some analysis (even then I prefer R/Python libraries for visuals). So I do have sympathy for wet-lab researchers who rely heavily on Excel.
From paragraph 10: