My name is Doug Speed and I am
a researcher at University College London Genetics Institute,
and today I will be telling you about heritability and its uses and hopefully,
I'll convince you why this is the most exciting area in quantitative genetics.
So there are two parts to this talk.
First, I'll tell you about
traditional heritability analysis and then I'll talk to you a bit
about SNP-based heritability analysis which is
a very recent era in the last five years and hopefully,
I'll give you an idea of all the uses it has in trying to understand complex traits.
So first of all, here a few books and papers which I find very useful.
The first one is "Introduction to Quantitative Genetics" and this
has more details of a lot of the first part of this talk.
The second to "Introductory Statistics with R" and "Elements of Statistical Learning".
Both available with the author's webpages to view online and then
here major papers in the field of SNP-based heritability analysis.
So it'll be useful for later.
First, traditional heritability analysis.
So heritability is a fundamental concept in quantitative genetics.
Really if you plan to do a genetic analysis of a phenotype,
one of the first thing you should think about is what is
the heritability of a trait you wish to study.
If heritability is zero,
then there's no point doing a genetic analysis.
Because there are no genetic factors influencing the trait.
Whereas if the heritability is very high,
then this suggests your analysis is likely to be fruitful.
We're often interested in very broad comparisons.
So for example, heritability,
tells us how well we might predict a particular trait.
So this could be in plant and animal genetics or it could be in human diseases.
So for example, if there's two diseases and one has
heritability 20 percent and one has heritability 80 percent,
then in theory, we could predict the second disease better than the first.
So it's probably a good reason to try and study with the second trait.