Comparison of 'DNA' Testing from 5 Companies

You decide how accurate these tests are.

Below is my video showing screenshots from five ‘DNA’ test results for the same person- from Circle DNA, Family Tree DNA, 23&Me, Ancestry, and My Heritage:

These screenshots are from this UsefulCharts video, and I was astounded by the disparity among the 5 tests:

What if you sent your drinking water samples to 5 different companies, and they came back with results of 26, 69, 25, 46, and 38% for some parameter, but they all used different methods? I am using Britain and Ireland for these numbers, but each company categorizes regions differently. How could you make sense of any of that? Why is it that they cannot use the same protocols and methods, the same regions, etc.? How can you break up a region into something small like Ireland vs something larger like Scandinavia?

Here are the screenshots, so you decide. Connect the dots on how they can determine anything from PCR Tests, genomic sequencing, etc. This is another example of showing something completely off, and the masses just lap it up. Just read all of the positive comments in the UsefulCharts Youtube video above. I know, a huge percentage of ‘users’ on social media are bots or troll farms, but still. This disconnect and gullibility is why they are addicted to getting away with blatant lies, so part of the blame with the state of the world is with the masses, not just the parasitic controller class. Just keep in mind, your data goes into their databases. You know who owns 23&Me and these other companies, right?

Northwestern European: 26.17% for Circle DNA

England and Ireland: about 69% for Family Tree DNA

British & Irish: 24.5% for 23&Me

England & Northwestern Europe & Ireland: 46% for Ancestry.com

English & Irish, Scottish, and Welsh: 37.9% for My Heritage

Addendum:

I highly recommend this article from Toby Rogers:

Nearly everything that we've been told about genes and autism is wrong

Some quotes from the article:

In the early 2000s, researchers were largely limited to candidate gene association (CGA) studies. These studies are relatively inexpensive to conduct and begin with likely genetic targets (usually because they have been associated with disease in previous human or animal studies) and then test human subjects who have that disease to see if those same DNA sequences show up (Patnala, Clements, and Batra, 2013). More than 600 associations between particular genes and various disease were reported (Hirschorn et al. 2002). But the replication rates were abysmal. Hirschorn et al. (2002) found that only 3.6% of reported associations were successfully replicated (and even there, the usual caveat applies that correlation does not equal causation).

Soon however, the cost came down on genome sequencing and hundreds of genome wide association (GWA) studies were launched to identify the genes associated with about 80 different diseases (Latham and Wilson, 2010). As the name suggests, a GWA study compares the entire genome between different individuals and looks for associations between common traits and particular DNA sequences (Hardy and Singleton, 2009).

The first GWA was published in 2005, and by 2009, 400 genome wide association studies had been completed at a cost of several million dollars each; but they yielded almost nothing of use (Wade, 2010). Goldstein (2009) in NEJM wrote that genomic research was “packing much less of a phenotypic punch than expected” (p. 1696). Wade (2010) wrote, “Indeed, after 10 years of effort, geneticists are almost back to square one in knowing where to look for the roots of common disease.” Lewontin (2011) wrote, “The study of genes for specific diseases has indeed been of limited value.”

Talbott (2013) provides some helpful new conceptual metaphors that better reflect the current state of thinking in genetic research.

Signaling pathways are vital means of communication within and between cells. In the machine model of the organism, such pathways were straightforward, with a clear-cut input at the start of the pathway leading to an equally clear-cut output at the end. Not so today, as a team of molecular biologists at the Free University of Brussels found out when they looked at how these pathways interact or “crosstalk” with one another. Tabulating the cross-signalings among just four such pathways yielded what they called a “horror graph,” and quickly it began to look as though “everything does everything to everything.” In reality, we see a “collaborative” process that can be “pictured as a table around which decision-makers debate a question and respond collectively to information put to them.” (Dumont et al., 2001; Levy et al. 2010).... “The activated receptor looks less like a machine and more like a pleiomorphic ensemble or probability cloud of an almost infinite number of possible states, each of which may differ in its biological activity” (Mayer et al., 2009, p. 81) (in Talbott, 2013, p. 52).

In more recent genetics research one sees the same entity express itself in different ways. Talbott (2013) writes, “[T]he ‘same’ proteins with the same amino-acid sequences can, in different environments, ‘be viewed as totally different molecules’ (Rothman, 2002, p. 265) with distinct physical and chemical properties” (p. 53).

Talbott (2013) argues that the static, mechanistic, and deterministic metaphors that are used in the popular press do not reflect the latest thinking amongst geneticists themselves.

With all of the ‘genetic’ information gathered by Anne Wojcicki’s 23&Me, her sister, Susan Wojcicki of Youtube/Google could not be saved:

23&Me is collapsing: turns out, all that precious DNA data is worthless.

Here’s a quote from Jamie Andrews’s article about how they had to change ‘antigen’ COVID tests:

DIY Controls

BBC Article

During the height of the Scamdemic there was information that was very quickly spread amongst kids at school that if you put Coca Cola on a Rapid Antigen Test for “Covid 19” it “breaks” it and they could get however long off school they wanted!!! How cool is that. These kids literally came up with a control experiment of their own, they found a substance that couldn’t possibly contain a virus because it was considered sterilized. They put it on the stick test which is considered “Antibody specific” and generated a positive result.

A bunch of kids not only conducted a control experiment, they falsified the test entirely. Not only that, they marketed this information using TikTOK and other social media platforms to all the other kids in other schools around the country in the UK. It really was Science 2.0 in action.

It was SO effective the entire establishment had to scramble and put out a section of published peer reviewed science to try and debunk these kids!

In this published paper they tried to claim the acid in the coca cola was causing the tests to be positive… unfortunately, they actually proved their theory wrong as it tested positive with bottled water, sparkling water and even vodka which is pH neutral!!

And he details accounts of dogs, bearded dragons, etc., etc., being sampled and returning human results, etc., as we’ve all heard by now. RIP John Magufuli, as well as other brave leaders.

A quote from Rupert Sheldrake’s Morphic Resonance, and this is from 2009:

The old assumption that life would be understood if molecular

biologists knew the “program” of an organism is giving way to a realization that

there is a huge gap between gene sequences and the way living organisms grow

and behave...

After the biotech bubble burst in 2000, many companies that

were part of the biotechnology boom of the 1990s either went out of business or

were taken over by pharmaceutical or chemical corporations. Several years later

the economic outcomes were still disappointing. An article in the Wall Street

Journal in 2004 was entitled “Biotech’s Dismal Bottom Line: More than $40

Billion in Losses.” It went on to say, “Biotechnology . . . may yet turn into an

engine for economic growth and cure deadly diseases. But it’s hard to argue that

it’s a good investment. Not only has the biotech industry yielded negative

financial returns for decades, it generally digs its hole deeper every year.”

Despite its disappointing business record, this vast investment in molecular

biology and biotechnology has had wide-ranging effects on the practice of

biology, if only by creating so many jobs. The enormous demand for graduates

in molecular biology and for people with doctorates in this subject has

transformed the teaching of biology. The molecular approach now predominates

in universities and secondary schools. Meanwhile, leading scientific journals

such as Nature are replete with glossy full-page advertisements for genesequencing

machines, protein-analysis systems, and equipment for cloning cells.

Precisely because there has been such a strong emphasis on the molecular

approach, its limitations are becoming increasingly apparent. The sequencing of

the genomes of ever more species of animals and plants, together with the

determination of the structures of thousands of proteins, is causing molecular

biologists to drown in their own data. There is practically no limit to how many

more genomes they could sequence or proteins they could analyze. Molecular

biologists now rely on computer specialists in the rapidly growing field of

bioinformatics to store and try to make sense of this unprecedented quantity of

information, sometimes called the “data avalanche.” But in spite of all this

information, the way in which developing organisms take up their forms and

inherit their instincts remains mysterious.

And here’s what I wrote in my article about what we think we know:

‘Junk DNA’, they tell us, is 98% of the total DNA, with hardly anything known about it (The term ‘junk’ should tell you something- move along, nothing to see here.). But what is DNA, exactly? A pet peeve: why can’t artists ever get the number of base pairs per helical twist correct, per their theories? The orthodox answer is five base pairs per twist. The best electron microscope images we have of ‘DNA’ are these images:

From https://northerntracey213875959.wordpress.com/2021/06/30/the-amino-age-and-the-new-abnormal-doctors/

The field of genetics is in shambles- they said 100k genes in humans, then 50k, then 20k, now down to 10k, and for over 180k known proteins and counting! Ulrich Bahnsen, in Genetics: Genome in Dissolution, states that in 2006,

25 geneticists sat down at the University of California at Berkeley to answer this seemingly simple question: What is a gene? However, the attempt to define the basic concept of their field precisely proved to be extremely difficult. The expert meeting almost ended in disaster, recalls Karen Eilbeck, Professor of Human Genetics at Berkeley and host of the round table: "We had meetings for hours. Everyone was screaming at everyone else."

Thanks for reading.