Understanding Genetic Analysis
There are three methods of genetic analysis available today. The first way is sequencing, or breaking down your DNA into every single piece of information to spell out everything. It tells you the order of all your genetic information. It requires a lot of money and time to process all of the information. You have about five billion nucleotides (chemical bits of information) in your whole genome. The cost of sequencing the whole genome can be several thousands of dollars. Instead of sequencing the whole genome, some companies will look at specific genes that are a concern for a fraction of the cost. For example, cancer or other genetic disorders. When you sequence a gene you will not miss any information on that gene related to why it might be involved in the cancer. Usually people only do this when they have already had a cancer diagnosis and want to know more about their genetics regarding that particular cancer. If you know you have a particular disorder, the safest way to go is to a specialty company that can tell you exactly what is going on with that by sequencing the genes related to that particular disorder.

The second way to analyze your genetics is called a DNA fingerprint. This isn’t used to determine your health because it doesn’t analyze genes, only parts of DNA that are non-gene coding. Just like a thumbprint is an identifier, your DNA fingerprint is a unique identifier for forensics, paternity tests, disaster identification, and historical investigations. DNA fingerprinting would be a more accurate marker for ancestry instead of population migrations pathways, but is not typically used as such.

The third way is the DNA microarray. This is how your genetic information is run at Ancestry DNA or other similar companies. A DNA microarray is a genetically printed chip that looks for the most common mutations in the human species. If the mutation is not printed on the chip, it will not be detected in the analysis. So the trade-off is the chips are cheap to make and run an analysis, but they miss data included in sequencing if they are not specifically looking for it. These chips were initially made for detecting cancer genes and enzyme metabolism to determine predispositions to adverse reactions to cancer treatments. Because the data is based on common mutations among various ethnic groups in our species, they can be used to access your ancestry and heritage as well as determine certain metabolic functions. Not all mutations are relevant. Some cause little to no change in the function of that gene. It’s like having your house painted blue versus white. Other mutations of the gene change its function. The difficulty in any genetic analysis is that we are not purely genetics. The environment plays as much if not a greater role in our overall health. But, the gene mutations do show our susceptibility to our environment. Example, a house made of brick versus a house made of Styrofoam. All things being equal you can live in both. But the moment a storm or disaster comes, the weaker house will have problems. The other problem with analyzing genetics is how complicated it is understanding how everything works together. You can make brownies with oil or butter and the end result doesn’t taste very different. But when you substitute salt for sugar you will notice the difference very time. Some genes can compensate for mistakes in other genes. The DNA microarray will basically tell you the most common mistakes you have and will allow you to know your sensitivity to certain environmental factors, foods, stresses and general drug metabolism. Your sex matters as well. Male or female hormones can make certain genetic problems more prominent. For example there are genes that are only expressed in ovaries. If you are male with that mutation, there most likely will be no problematic outcome. Hormone imbalances can also influence your genes depending on your sex. The body does a good job of taking what it needs from where it needs it, especially if there are one or two genetic mutations stressing out the system. So the more complicated analysis is understanding how the general biochemistry in your body works. Certain supplements that benefit one person may be harmful to another because of the combined effects of their overall metabolism.

When you buy a car, it comes with an owner’s manual for maintenance and repair purposes. When you have an accurate DNA analysis, it works much like that owner’s manual for current and future reference. A simple headlight goes out it is easy to fix, but engine problems require a much more thorough diagnostic. The same goes for the human body. Vitamin B deficiency is very easy to fix, but something like cardiovascular health is a much more complicated issue.
Your DNA analysis is not meant to be a diagnosis, but to give you clues as to what future tests you may need and to eliminate guesswork as to which supplements and medications will be most beneficial for your unique body. Always consult a doctor or health care professional when going off of or starting medications or supplements. Your doctor will know more about the environmental factors that should be considered.

Causative VS Correlative Data
This is what makes a Somaticode report different from all other report. The DNA microarray will give both relevant and irrelevant information regarding your genes related to health. Many of the studies that have been done thus far by other genetic analysis companies have been correlative in nature, meaning they will take the genetic information from people in a specific demographic and correlate them to mutations with the highest frequency in that pool of people. That doesn’t mean those mutations are the cause of that specific disorder. They are merely correlated with people who fit that criteria for that specific disorder. Many diagnostics unfortunately are based on these correlative studies. The Somaticode analysis fundamentally looks at the function of the gene that has been shown to have an actual change in the gene’s behavior. This increases the confidence that there is a higher causative association rather than correlative. The difference between correlative and causative can be illustrated by the following example. Shark attacks increase as ice cream sales increase, therefore increase ice cream sales are associated with increase shark attacks. This is an example of correlative data. Looking at the cause would require looking around at other factors like the summer season, which is more likely to be causing both an increase in ice cream sales as well as an increase in shallow swimming behavior that would lead to higher shark attacks. Sometimes because people share common ancestry due to ethnicity, they share genes that cause disorders and other genes that are now correlated with the disorders. We leave as much correlative data out as we can. There are still mutations that are being reviewed or have conflicting results of pathogenic significance. Until such time as these conflicting reports can be further analyzed, we have kept them in because they may still be relevant.