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Population structure is controlled through the use of the structure as a co-factor in the analyses. They use a principal component analysis on the genotypes to

by Real_S 9y ago

Population structure is controlled through the use of the structure as a co-factor in the analyses. They use a principal component analysis on the genotypes to estimate the structure, and then use the first few principal components (PCs) as cofactors in the analyses. So if the European population they used consisted of half English and half French participants, then the first PC would likely divide the two. So if British or French ethnicity affected the analysis, this effect would be reduced or eliminated using just the first PC. How many PCs should be used? Well, ten is a common number chosen. Is it enough? Probably for most studies including this one. So ancestry and ethnicity in this type of research emerges purely from a PC analysis on the genotypes. They do not use self-reported ethnicity or any other type of common ethnic grouping. To control for population structure, self-reported ethnicity is rarely useful. Its far too unreliable. But these groupings do sometimes loosely correspond to the PCs found in the analysis, supporting the use of PC as a method to control for ethnicity.

subroutine 9y ago
Do you believe these findings though? (original article: http://www.pnas.org/content/111/Supplement_3/10796.full http://www.pnas.org/content/111/Supplement_3/10796.full ) To me there are a few things worth highlighting, that are at least tangentially relevant: 1. This article was a PNAS Direct Submission. PNAS Direct Submission, a privilege typically reserved for members of the National Academy of Sciences, is like using trump-card to basically skip peer review. Since NAS members are usually great scientists with a track-record of publishing in high-impact peer reviewed journals, PNAS Direct Submissions are usually saved for pet-projects where the underlying science is... mmmm... of dubious quality. This is not always the case, but when all-star scientists opt for PNAS DS, it's certainly a reason to be speculative. 2. Nick Christakis and James Fowler have teamed up for a number of fancy-ass studies (the type that ensure people will want to write wikipedia pages about them, and lead to TED talk invites); some suggesting personal attributes like obesity, smoking, and happiness arise via 'social contagion', that is, behavioral propensities are transmitted over social networks. And studies like this one, where they find friendship affinities embedded in the genome. 3. I recently read a genome-wide association study (GWAS) with over 400 authors (https://www.ncbi.nlm.nih.gov/pubmed/28714976 https://www.ncbi.nlm.nih.gov/pubmed/28714976). I think 400 authors is way above median, but even relatively tame GWAS typically require a group effort just for data QC. Here, somehow these two guys did it all themselves. 4. Not only did they find that some SNPs were positively correlated, they also found some that were negatively correlated... "Across the whole genome, friends’ genotypes at the single nucleotide polymorphism level tend to be positively correlated (homophilic). In fact, the increase in similarity relative to strangers is at the level of fourth cousins. However, certain genotypes are also negatively correlated (heterophilic) in friends. And the degree of correlation in genotypes can be used to create a “friendship score” that predicts the existence of friendship ties in a hold-out sample." So the HN/Nature title might as well be: "Friends are Genetically similar, and Genetically Different".
- Real_S 9y ago
  1. You are perceptive, this is usually something to watch out for. However, it does not always indicate that a study is flawed, just that the research might have met with unwanted resistance, and the authors are in position to avoid that resistance. 2. Yes, these scientists are looking to make their research popular, highlighting an unfortunate conflict of interest present in academia. They do this to get big grants. Important observation, but insufficient to dismiss a finding out of hand. 3. So many authors, such a joke! These people mostly just help collect data, or sometimes simply share data they already have and then give the manuscript a quick read before publishing. But that is actually beside the point. If a lab already had data ready, and isn't pressured to add authors for political reasons, then two authors is not necessarily a red-flag. In fact, these analyses are relatively easy to do with available software. If they have the data, they just plug and chug. 4. The findings of the paper suggest strongly that friends are more genetically similar, on average, akin to fourth cousins. The results have yet to be rebutted to my knowledge. The fact they found some regions were negatively correlated does not conflict with their overall results. I have some doubts that their regional analyses should carry much weight (e.g. olfactory and immune regions). Furthermore, their explanations using natural selection appear to be a stretch. These are possible overstatements of results, allowed because of your points 1 and 2. My overall impression of the paper is that main results are somewhat interesting and entirely novel. But there is a ton of stretching for just-so stories and "interesting" findings that will be unlikely to hold up. Typical PNAS.
  - subroutine 9y ago
    Thanks for these replies. Also, very cool idea you have here: Cryptography for genetic material
- NewRapGod 9y ago
  You seem to not like the result of the study and making non-arguments to try to discredit it.
  - subroutine 9y ago

by Real_S 9y ago

subroutine 9y ago

Do you believe these findings though? (original article: http://www.pnas.org/content/111/Supplement_3/10796.full http://www.pnas.org/content/111/Supplement_3/10796.full ) To me there are a few things worth highlighting, that are at least tangentially relevant: 1. This article was a PNAS Direct Submission. PNAS Direct Submission, a privilege typically reserved for members of the National Academy of Sciences, is like using trump-card to basically skip peer review. Since NAS members are usually great scientists with a track-record of publishing in high-impact peer reviewed journals, PNAS Direct Submissions are usually saved for pet-projects where the underlying science is... mmmm... of dubious quality. This is not always the case, but when all-star scientists opt for PNAS DS, it's certainly a reason to be speculative. 2. Nick Christakis and James Fowler have teamed up for a number of fancy-ass studies (the type that ensure people will want to write wikipedia pages about them, and lead to TED talk invites); some suggesting personal attributes like obesity, smoking, and happiness arise via 'social contagion', that is, behavioral propensities are transmitted over social networks. And studies like this one, where they find friendship affinities embedded in the genome. 3. I recently read a genome-wide association study (GWAS) with over 400 authors (https://www.ncbi.nlm.nih.gov/pubmed/28714976 https://www.ncbi.nlm.nih.gov/pubmed/28714976). I think 400 authors is way above median, but even relatively tame GWAS typically require a group effort just for data QC. Here, somehow these two guys did it all themselves. 4. Not only did they find that some SNPs were positively correlated, they also found some that were negatively correlated... "Across the whole genome, friends’ genotypes at the single nucleotide polymorphism level tend to be positively correlated (homophilic). In fact, the increase in similarity relative to strangers is at the level of fourth cousins. However, certain genotypes are also negatively correlated (heterophilic) in friends. And the degree of correlation in genotypes can be used to create a “friendship score” that predicts the existence of friendship ties in a hold-out sample." So the HN/Nature title might as well be: "Friends are Genetically similar, and Genetically Different".

Real_S 9y ago
1. You are perceptive, this is usually something to watch out for. However, it does not always indicate that a study is flawed, just that the research might have met with unwanted resistance, and the authors are in position to avoid that resistance. 2. Yes, these scientists are looking to make their research popular, highlighting an unfortunate conflict of interest present in academia. They do this to get big grants. Important observation, but insufficient to dismiss a finding out of hand. 3. So many authors, such a joke! These people mostly just help collect data, or sometimes simply share data they already have and then give the manuscript a quick read before publishing. But that is actually beside the point. If a lab already had data ready, and isn't pressured to add authors for political reasons, then two authors is not necessarily a red-flag. In fact, these analyses are relatively easy to do with available software. If they have the data, they just plug and chug. 4. The findings of the paper suggest strongly that friends are more genetically similar, on average, akin to fourth cousins. The results have yet to be rebutted to my knowledge. The fact they found some regions were negatively correlated does not conflict with their overall results. I have some doubts that their regional analyses should carry much weight (e.g. olfactory and immune regions). Furthermore, their explanations using natural selection appear to be a stretch. These are possible overstatements of results, allowed because of your points 1 and 2. My overall impression of the paper is that main results are somewhat interesting and entirely novel. But there is a ton of stretching for just-so stories and "interesting" findings that will be unlikely to hold up. Typical PNAS.
- subroutine 9y ago
  Thanks for these replies. Also, very cool idea you have here: Cryptography for genetic material
NewRapGod 9y ago
You seem to not like the result of the study and making non-arguments to try to discredit it.
- subroutine 9y ago