Good introductory biology/genetics readings for statisticians? I'm looking for books on genetics or biology in general, at an introductory level, ideally where topics are tackled from a statistical point of view. I've been reading "Genes population and languages" by Luca Cavalli-Sforza these last few days and I'm enjoying it a lot, something similar would be perfect.
To give you some background information, I'm a graduate student in biostatistics, recently switched to biostats from economics, so I don't know much about biology in general. I'm trying to get an idea of the field in order to decide wether to take courses in statistical genetics or spatial analysis.
Thank you!
 A: Not sure exactly what you want.  Not too specialized, I think, and with some biological content, but also statistical.  I don't know spatial analysis, but have collaborated with statistical geneticists, which gives me a distorted view of the field.


*

*The two-volume Handbook of Statistical Genetics.

*You might want to consider just constructing your own textbook by choosing articles from Nature Reviews Genetics and other sources of good review articles.  NRG articles, for example, are designed to introduce ideas from one area of biology to people in another area who don't know anything about the first one.  That and the web might be all you need.

*Population genetics and related textbooks: All have some statistical material, I'd say, but some focus more on models of evolutionary processes than statistical inference about them.  That said, I think there are parts of statistical genetics that take for granted understanding of those models, and population genetics textbooks will all include a bit of biological content relevant to genetic data.
A. Less statistical:
Hartl & Clark: A classic, with relatively easy math embedded in discussion of principles and examples.  Widely used.
Gillespies' Population Genetics: A Concise Guide: Quick survey of key models and concepts in population genetics.  Great book that I have turned to repeatedly.  Covers topics such as the evolution of sex not usually covered in an introduction.
Rice's Evolutionary Theory: Mathematical and Conceptual Foundations: Deeper and broader than Gillespie, and conceptually more interesting, I feel.  Also a great book, and also covers some topics not usually covered, such as Price's equation, multilevel selection, and complex epistatic interactions.
Ewens' Mathematical Population Genetics I: This is a serious and pretty thorough mathematical survey of several core areas of population genetics.
Nagylaki's Introduction to Theoretical Population Genetics: Easier than Ewens, harder than the first three.  Covers some material not usually covered, such as more than 3 and fewer than an infinite number of alleles.
B. The quantitative genetics part of population genetics tends to focus more on statistical inference:
Lynch and Walsh Genetics and the Analysis of Quantitative Traits
Falconer & McKay Introduction to Quantitative Genetics
I personally like L&W more than F&M, but F&M is good.  Very widely cited.  Now in its Nth edition.
C. More statistical, conceptually deep, but with somewhat idiosyncratic focus:
Bruce Weir's Genetic Data Analysis II: Unusual approaches but very interesting.  Nice conceptual background for relationships between measures of population structure and ANOVA, for example.
Masatoshi Nei's 1987 book:  Covers a lot of ground, and is still cited.  His more recent book with Kumar is also worthwhile.  The latter has more recent material, as you'd expect, but sometimes just refers back to the 1987 book for proofs.  Both have quite a bit of biological content discussed along the way.  Both focus on phylogenetic inference as well as population genetical matters.
D. If you decide to learn more about coalescent theory, which is widely used for modeling and statistical inference about genetic data:
Wakeley's Coalescent Theory

*Phylogenetic inference is sometimes relevant to statistical genetics, involves a variety of statistical methods (and debates between their partisans):
Felsenstein, Inferring Phylogenies

*Statistical inference plays central roles in parts of bioinformatics.  I'm only familiar with Ewens & Grant's Statistical Methods in Bioinformatics.  A great book, although a lot of the material will be review, and I would worry that it's out of date.
Or you could go old-school, and read Fisher's The Genetical Theory of Natural Selection, which could be fun.  Some of the arguments in the book were only fully worked out in the last couple of decades.  Or read Sewall Wright's books.  Or Gustave Malecot.  These works are old but still relevant.
[Edited from previous, disorganized version.]
A: Just five chapters into Paige Harden's new book. Enjoying it but she has a high bar to clear
https://lareviewofbooks.org/article/why-dna-is-no-key-to-social-equality-on-kathryn-paige-hardens-the-genetic-lottery/
