In GWAS you are looking for statistical asociations between your SNPs and genes that are potentially coding for your trait. This asociation is found when your SNP and gene are in tight linkage, but it does not mean it is the only gene your SNP is linked to. So you will always have to investigate which of the genes in that area is actually causally correlated to your trait. It can be that there are also other genes in that area that are do not have anything to do with your trait.
you gave a thorough explanation 💯
I'm doing self study on what a GWAS is for work, and this helps me understand it better. Thanks!
Excellent! Extremely clear and helpful!
Gotta point the most important parts for future viewers.
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Finally!!! finally I understood this!! Amazing video so well explained so clearly put!! thank you sm!!!
Easy understanding explanation, thank you so much!
Thank you ! great explanation
very simple and understandable. thank you very much
Thank you so much! an amazing video helped me a lot :)
good way to teach
Thanks for the concept
Great video!
You are goated
I have a question: Why GWAS cannot tell the specific gene as we put both the genes (SNPs) and trait into the model?
In GWAS you are looking for statistical asociations between your SNPs and genes that are potentially coding for your trait. This asociation is found when your SNP and gene are in tight linkage, but it does not mean it is the only gene your SNP is linked to. So you will always have to investigate which of the genes in that area is actually causally correlated to your trait. It can be that there are also other genes in that area that are do not have anything to do with your trait.
How can you carry out the manhattan plots?
I use the R package qqman