I have DNA results from 23andMe, FTDNA and Circle and have now ordered Nebula´s whole genome of my DNA. How do I justify ordering that?
DNA results may be compared with purchasing some literature: 23andMe is like a precis, Circle may be thought of a book with several chapters missing and FDNA is a detailed small book on a specific topic.

To elaborate, 23andMe covers only about 700,000 locations of the 3.2 billion, but these have been chosen carefully from all the chromosomes plus MT for their genetic importance.

Circle covers much more of the DNA, about 50 times 23andMe; 31 million datapoints- but has much redundancy - the locations don´t have documented SNPs. Circle claims to cover all Exomes -the protein making locations. (I have often found SNPs covered by 23andMe but not Circle).

Nebula covers all of the genome: 3.2 billion locations or 6.4 billion letters, base pairs - that is all the SNPs, insertions and deletions for all chromosomes and MT. It is future proofed because as research continues new mutations will be found and SNPs added to the database.

I have downloaded and unzipped, where necessary, the data files from all 4 DNA data sequencers. They are here:

23andMe         5099KB csv,txt
Circle - Premium     1939736KB csv,txt
Nebula Genomics114177936KB CRAM (BAM)
Nebula Genomics101984099KB FASTQ R1
Nebula Genomics113579733KB FASTQ R2
Nebula Genomics   1211219KB vcf
FTDNA - Big Y 700     656638KB BAM

I have set up a bookmark for Nebula: https://portal.nebula.org/reporting/library   I´ve found the Library, Gene Analysis and Genome Browser along with SNPedia and NCBI website very useful.
SNPedia address is: https://www.snpedia.com/index.php/rs4340. I have chosen the RsID4340 at random. The actual one of interest replaces the numerical part.
The US National Library of Medicine relates locations, Rs IDs and mutations (insertions, deletions,rsIDs,gene names and more.. https://www.ncbi.nlm.nih.gov/genome/gdv/browser/gene/?id=1   The ?id=1 is needed to open the site. The Assembly needs to set to GRCh38 (the latest version) and the Search box is located under Genome Data Viewer.


The Library has 280 personalsed reports for me to view (as of January 2022). I usually view them sorted high to low polygenic score after glancing at newly added items. I like the short introduction to the topic then the table of risk SNPs. There is also a relative percentage figure given to my genetic predisposition to the topic. This is, of course, relative to others tested by Nebula but all other sections are based on science research.
From the Library I usually choose the SNP with the most effect on a condition and copy that rsID to the NIH application. If that gives a gene I copy that to Nebula Gene Analysis tool. That may indicate the severity or otherwise of the mutation. Now for an actual example - age related macular degeneration (ARMD). I uploaded 23andMe results to Codegen. This is a part of Codegen´s report:
rs10490924(T;T) bad:4.27 8.21% 8.2x risk for age related macular degeneration.
rs10490924 , also known as c.205G>T, p.Ala69Ser and A69S, was identified as a risk factor from chromosome 10 related to age related macular degeneration. The risk allele is (T). Odds ratios for heterozygotes and homozygotes are, respectively, 2.69 (CI: 2.22-3.27) and 8.21 (CI: 5.79-11.65).
Disease risk in combination with the rs1061170 SNP in the CFH gene is dramatically increased. Homozygotes for both the rare/risk alleles at both loci are estimated to be at 57 fold higher risk for age related macular degeneration than individuals homozygous for the common alleles at both loci. A subsequent study indicated that the risk based on solely the ARMS2 SNP rs10490924 is significantly higher in smokers than in non-smokers. . . . . . . This is only about 10% of the commentry.
rs11200638(A;A) bad:4.20 8.38% ~10x increased risk of wet age related macular degeneration To minimize your risk of age related macular degeneration, consider a diet rich in vitamins C and E, lutein, zeaxanthin and the minerals zinc and copper, such as kale, spinach and broccoli. source rs11200638 , a SNP in the HTRA1 promoter, is associated with a 10 fold increased risk of wet age related macular degeneration in Japanese and Caucasian populations. Further confirmed [PMID 18207215, PMID 18206206]. The genotype at highest risk is (A;A). Note, most studies have shown that that this SNP is highly predictive (i.e. is in near perfect (D'>0.98) linkage disequilibrium) with rs10490924 , thus the status of one very closely predicts the status of the other. However, one Caucasian AMD study reported the linkage disequilibrium measure for these two SNPs on 10q26, (i.e., rs10490924 , which is upstream of HTRA1 in LOC387715/ARMS2, and rs11200638 ) as D'=0.8, and all four possible haplotypes of the two SNPs were detected in the samples. Further, this same study reported that these two SNPs appear to contribute equally to the risk of AMD (both GA and CNV) and show no evidence of interaction with CFH. A 2011 meta-analysis concluded that rs11200638 (A;G) and (A;A) carriers had 2.243 and 8.669 times the risk of developing AMD, respectively, when compared with those who carry the (G;G) genotype. rs10490924 and rs11200638 defined 2 significant haplotypes associated with increased risk of neovascular AMD. show that rs11200638 has no significant impact on HTRA1 promoter activity in three different cell lines, and HTRA1 mRNA expression exhibits no significant change between control and AMD retinas.
As mentioned above this is only part of the documentation - some detail!
A number of other SNPs are mentioned including rs5888, rs1061147, rs800292, rs380390 and rs9821532.

 

NebulaARMD ContinuedThis genome-wide association study attempted to identify genetic variants that correlate with a person’s risk of developing this age-related macular degeneration by examining the genomes of over 40,000 individuals of European ancestry. The study found 34 genetic loci, 16 of which are novel, that are associated with age-related macular degeneration. Some of the implicated genes play a role in the formation of extracellular matrix, that embeds the eyes and other organs. Other implicated genes are known to be involved in inflammation control. DID YOU KNOW? Smoker’s have a significantly increased risk of developing macular degeneration. When the chemicals from cigarette smoke get in the eyes, they irritate the retina and can cause lasting damage over time. [SOURCE] YOUR DETAILED RESULTS To calculate your genetic predisposition to age-related macular degeneration we summed up the effects of genetic variants that were linked to age-related macular degeneration in the study that this report is based on. These variants can be found in the table below. The variants highlighted in green have positive effect sizes and increase your genetic predisposition to age-related macular degeneration. The variants highlighted in blue have negative effects sizes and decrease your genetic predisposition to age-related macular degeneration. Variants that are not highlighted are not found in your genome and do not affect your genetic predisposition to age-related macular degeneration. By adding up the effect sizes of the highlighted variants we calculated your polygenic score for age-related macular degeneration to be 1.44. To determine whether your score is high or low, we compared it to the scores of 5,000 other Nebula Genomics users. We found that your polygenic score for age-related macular degeneration is in the 93rd percentile. This means that it is higher than the polygenic scores 93% of people. We consider this to be a high genetic predisposition to age-related macular degeneration. However, please note that genetic predispositions do not account for important non-genetic factors like lifestyle. Furthermore, the genetics of most traits has not been fully understood yet and many associations between traits and genetic variants remain unknown. For additional explanations, click on the column titles in the table below and visit our Nebula Library tutorial.
The table below gives the data of the first half of the tested SNPs (There are 32 in total).
N/A indicates variants that could not be imputed using the 1000 genomes project datasets and variants that have a frequency of < 5%. Your genome was sequenced at 30x/100x coverage and is not imputed. However, to calculate percentiles, we need to compare your data with other users imputed data. To make the data comparable, we need to exclude some of the variants from your data.
ADDITIONAL RESOURCES: Vision (Video), Age-related Macular Degeneration.
This last item is a link to the American Academy of Ophthalmology - interesting.

What next? I could check the genes involved. SNpedia does not cover recent RsIDs so I usually use the NCBI site mentioned above. Currently I have only a very small area of the macular that may cause fuure problems.

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