Discussion in 'Genetic Testing and SNPs' started by Valentijn, Oct 25, 2013.
Great idea!! Thanks for doing this, I know it's a LOT of work!
This information has the potential to be very important to many of us. It seems to me that the next step is to get this to doctors/researchers who mayt be interested in pursuing the clues. At least some of these snps appear to have never been studied, and perhaps this information shows that they should be. It's a small amount of data, but very powerful results statistically - that must mean something!
With Valentijn's permission, I'm going to forward this to everyone in this field that I have contact information for. And followup some contacts that might be able to get this data to others with more resources.
Does anyone have a close communication channel to Lipkin? Any of the other big players? What about contacts with geneticists? Is there anyone who would like to writeup a quick description/summary of what this data is? We have some people here who are very talented writers.
So, Val - what do you think we should do with your data?
Would have been a boost if a majority of the 'Ps' had red in the same row. Still a mystery but very interesting just with our sample so far. Will be intersting if other CCC/ICC folks hsare there rare data. Thanks again Val for doing this.
@taniaaust1 Under the TT group did you mean 'rosie60' or me roxie60? We have a Rosie on the board so I just want to be sure who you mean to list under TT.
I noticed that too Roxie.
I nearly jumped when I saw it as for a moment I thought it was me
something i find interesting, so far majority of controls are male. if I recall more females get this diagnosis than males so we fit that expectation so far.
It's quite preliminary currently. A lot of shared SNPs haven't been added to the list yet, and some need to be double-checked to ensure that they do indeed have a pretty close relationship with AKT1. And then I need to verify the directions of those relationships - that they are affecting AKT1 and not vice-versa. Plus I want to look into a common gene or genes for other rare shared SNPs which are not leading to AKT1.
And then I need to make sure that there aren't thousands of genes having a pretty direct effect on AKT1, since these results would be somewhat less significant if that were the case. And this weekend maybe I can get some sort of database going to look at all of the public 23andMe files, as a better control set to make sure rare homozygous mutations aren't over-reported by 23andMe.
So I think it would be premature to do anything with the data at this point, aside from poking it with a stick some more
Val, is the chart above just showing snps you think may be related to AKT1? And so there are other possibilities out there? Is there anything we non-scientists can help with?
One of the striking things about your chart is the avg. rare allele rate for the controls vs. the me/cfs group. I wonder how much of a gap there would be in the overall 1% or 10% report numbers.
Let us know if or when you want help getting any information out. And thanks so much for all your efforts!
UBC (ubiquitin C) is another gene which many of the SNPs can be traced back to ... but most of those SNPs are still closer to AKT1 than UBC. But since UBC and AKT1 have a direct impact on each other, that isn't surprising. If UBC is more relevant than AKT1, that should show up when examining how each gene is affecting the other genes.
It's hard to guess how significant that is. The SNPs were chosen because they are more common among ME/CFS patients in the samples I have, hence it's not too surprising that they're less common among the controls. Even if it's completely random that we have those SNPs, I'd still expect them to be less common among the controls. So I think some math might be required at some point to determine if those SNPs are likely to be statistically significant, given that we are selecting them from a huge number of SNPs (960,000). I'm not sure about the math involved, except that more samples showing the same trend = greater significance.
This particular observation looks like a classic preliminary false positive to me. *shrugs*
That's definitely a possibility. Which is why I think it's very necessary to dig into things more before getting too excited
Wow a graph!! I love graphs
You are doing a great job with putting this all together.
thanks for giving us an anonomous rundown of the types of ME/CFS patients which are giving what results.
I think that needs to be discounted as being important at all as this wasnt a blind study and these genes involved there have been picked up from lots as being the higher ones in us to start with.
That comparison would only be important if you now get a completely different group of ME/CFS patients and compare those with the controls and see if they are still high compared to them (see if you can come up with the same results again, that would be quite telling). If you did this, it may more quickly make it obvious that certain SNPs are probably on the wrong track if the two different groups of ME/CFS people show completely different result.. Would a separate group of say 8 ME/CFS people have the same genes highlighted as you have here?
I'll be excited to see what happens to these results as more people give their DNA data
One thing I'd like to point out is that I think that its important for the control group esp since genes are being compared, to not be blood related to the ME/CFS group. Are all this control group blood unrelated?
Im a bit sad, I was going to get you three more controls to add to this but due to the 23andME FDA thingy, they wont be now able to get the test.
The first post on this thread said the following "The rare allele is T. Thus far we have homozygous results for @allyb, @GypsyA, @roxie60," so it was roxie60 I was refering too as being TT.
So far the controls are all unrelated - they're from opensnp members who filled out that they do not have frequent pain or fatigue.
I've got about 450 more "controls" from opensnp members. They're ones who didn't fill out their profiles, but also didn't indicate that they have frequent pain and fatigue. But that's more than I can process manually, so my fiance/programmer is working on getting them into a database, so it's much easier to compare the ME/CFS patients to a huge group.
I'd also like to see some additional profiles for ME/CFS patients, to see how they fit into the potential pattern.
@Valentijn I still couldn't get my computer to run your program so I've looked these up manually. My results are in colours.
rs13118884 A AA
rs10457667 A AG
rs1338457 A AG
rs6799780 G GG
rs11791618 C TT
rs10735443 A AC
rs1946282 G AA
rs6816809 A AG
rs476951 A GG
rs11057369 A GG
rs4720309 A GG
rs4279979 G AG
rs17762542 G AG
rs5965630 A CC
rs6786329 C TT
rs2979001 T CT
rs2221513 G AA
rs952061 T CT
rs36880 C TT
rs137954 G AA
rs17780664 G AA
rs17133109 A GG
rs17321293 C TT
rs2417266 C CT
rs2139567 T CC
rs13133587 T CC
rs7912364 A AA
rs11907065 C AA
rs12732188 A GG
I meet the CCC
Thank you! I'll add you to the current list. I've also changed your rs6799780 to be flagged red since it looks like you have the minor allele for that one.
I managed to get one of your programs to run. Is this of any help?
It looks like those are results from the one_percent database. What I'm comparing are the results from the ten_percent database located at http://sourceforge.net/projects/analyzemygenes/files/Databases/ . You can download it, unzip it, and select it when running the "genes" program instead of one_percent. It creates a fairly big and spammy file, so it might be easiest to email it to me, if you're comfortable with that.
oh wow, I had no idea one could get info like that for a control group so easily.
You can also try a Google Site Search
Separate names with a comma.