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Recommended reading

Textbooks

Year Category Reference Why recommended
2020 Statistical Genetics An Introduction to Statistical Genetic Data Analysis By Melinda C. Mills, Nicola Barban and Felix C. Tropf https://mitpress.mit.edu/books/introduction-statistical-genetic-data-analysis A gentle textbook on genetic data and study design (including GWAS-style work and polygenic scores) for readers who want words and examples, not only equations.
2019 Statistical Genetics Handbook of Statistical Genomics: Fourth Edition https://onlinelibrary.wiley.com/doi/book/10.1002/9781119487845 A broad reference many chapters by experts—handy when you need depth on a specific method (association, relatedness, sequencing, etc.) beyond one short tutorial.
2009 Statistical Analysis and Machine Learning The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics). Trevor Hastie, Robert Tibshirani, Jerome Friedman. https://hastie.su.domains/ElemStatLearn/ (PDF book is available) Core statistics and prediction (regression, cross-validation, shrinkage, trees)—not genetics-only.

Overview Reviews

Core GWAS overview

Year Reference Link Why recommended
2021 Uffelmann, E., Huang, Q. Q., Munung, N. S., De Vries, J., Okada, Y., Martin, A. R., … & Posthuma, D. (2021). Genome-wide association studies. Nature Reviews Methods Primers, 1(1), 1–21. Journal A good first full guide: walks through how a GWAS is planned, analyzed, and read, and mentions ethics—written for newcomers, using today’s norms.
2019 Tam, V., Patel, N., Turcotte, M., Bossé, Y., Paré, G., & Meyre, D. (2019). Benefits and limitations of genome-wide association studies. Nature Reviews Genetics, 20(8), 467–484. PubMed · Journal Explains what GWAS is good for (finding risk regions, clues to biology) and what it is not (not every hit is a simple “gene for disease”). Stops hype and sets realistic expectations.
2017 Pasaniuc, B., & Price, A. L. (2017). Dissecting the genetics of complex traits using summary association statistics. Nature Reviews Genetics, 18(2), 117–127. PubMed For when you only have published summary results (betas, p-values, sample sizes)—how people still combine studies, compare traits, and narrow regions without individual-level genomes.
2008 McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P. A., & Hirschhorn, J. N. (2008). Genome-wide association studies for complex traits: consensus, uncertainty and challenges. Nature Reviews Genetics, 9(5), 356–369. PubMed An early “rule book” many groups agreed on: how to run a GWAS, repeat findings in new samples, and what was still unclear—helps you see why replication and careful design matter.
2006 Balding, D. J. (2006). A tutorial on statistical methods for population association studies. Nature Reviews Genetics, 7(10), 781–791. PubMed Builds basic statistics for beginners: how we test SNP–trait links, how hidden ancestry can fool you, and why testing millions of SNPs needs extra care.
2005 Hirschhorn, J. N., & Daly, M. J. (2005). Genome-wide association studies for common diseases and complex traits. Nature Reviews Genetics, 6(2), 95–108. PubMed Short origin story: why researchers switched from family/linkage scans to scanning the whole genome with SNP chips for common diseases.

GWAS milestone reviews (5-, 10-, and 15-year perspectives)

Year Milestone Reference Link
2023 15 years Abdellaoui, A., Yengo, L., Verweij, K. J., & Visscher, P. M. (2023). 15 years of GWAS discovery: Realizing the promise. The American Journal of Human Genetics, 110(2), 179–194. PubMed
2017 10 years Visscher, P. M., Wray, N. R., Zhang, Q., Sklar, P., McCarthy, M. I., Brown, M. A., & Yang, J. (2017). 10 years of GWAS discovery: biology, function, and translation. The American Journal of Human Genetics, 101(1), 5–22. PubMed
2012 5 years Visscher, P. M., Brown, M. A., McCarthy, M. I., & Yang, J. (2012). Five years of GWAS discovery. The American Journal of Human Genetics, 90(1), 7–24. PubMed

Topic-specific

Population structure and stratification

Year Reference Link
2010 Price, A. L., Zaitlen, N. A., Reich, D., & Patterson, N. (2010). New approaches to population stratification in genome-wide association studies. Nature Reviews Genetics, 11(7), 459–463. PubMed
2021 Diaz-Papkovich, A., Anderson-Trocmé, L., & Gravel, S. (2021). A review of UMAP in population genetics. Journal of Human Genetics, 66, 85–91. Journal

Replication and follow-up

Year Reference Link
2009 Ioannidis, J. P. A., Thomas, G., & Daly, M. J. (2009). Validating, augmenting and refining genome-wide association signals. Nature Reviews Genetics, 10(5), 318–329. PubMed

Meta-analysis

Year Reference Link
2009 Zeggini, E., & Ioannidis, J. P. A. (2009). Meta-analysis in genome-wide association studies. Pharmacogenomics, 10(2), 191–201. PubMed
2013 Evangelou, E., & Ioannidis, J. P. A. (2013). Meta-analysis methods for genome-wide association studies and beyond. Nature Reviews Genetics, 14(6), 379–389. PubMed

LD

Year Reference Link
2008 Slatkin, M. (2008). Linkage disequilibrium—understanding the evolutionary past and mapping the medical future. Nature Reviews Genetics, 9(6), 477–485. PubMed

Phasing and Imputation

Year Reference Link
2026 Sun, Q., & Li, Y. (2026). Advances in haplotype phasing and genotype imputation. Nature Reviews Genetics, 27, 155–169. Journal
2018 Das, S., Abecasis, G. R., & Browning, B. L. (2018). Genotype imputation from large reference panels. Annual Review of Genomics and Human Genetics, 19, 73–96. Journal
2011 Browning, S. R., & Browning, B. L. (2011). Haplotype phasing: existing methods and new developments. Nature Reviews Genetics, 12(10), 703–714. PubMed
2010 Marchini, J., & Howie, B. (2010). Genotype imputation for genome-wide association studies. Nature Reviews Genetics, 11(7), 499–511. PubMed

Heritability

Year Reference Link
2008 Visscher, P. M., Hill, W. G., & Wray, N. R. (2008). Heritability in the genomics era—concepts and misconceptions. Nature Reviews Genetics, 9(4), 255–266. PubMed
2009 Manolio, T. A., Collins, F. S., Cox, N. J., Goldstein, D. B., Hindorff, L. A., Hunter, D. J., … & Visscher, P. M. (2009). Finding the missing heritability of complex diseases. Nature, 461(7265), 747–753. PubMed
2014 Witte, J. S., Visscher, P. M., & Wray, N. R. (2014). The contribution of genetic variants to disease depends on the ruler. Nature Reviews Genetics, 15(11), 765–776. PubMed
2017 Yang, J., Zeng, J., Goddard, M. E., Wray, N. R., & Visscher, P. M. (2017). Concepts, estimation and interpretation of SNP-based heritability. Nature Genetics, 49(9), 1304–1310. PubMed

Genetic correlation

Year Reference Link
2019 van Rheenen, W., Peyrot, W. J., Schork, A. J., Lee, S. H., & Wray, N. R. (2019). Genetic correlations of polygenic disease traits: from theory to practice. Nature Reviews Genetics, 20(10), 567–581. PubMed

Fine-mapping

Year Reference Link
2025 Li, Z., & Zhou, X. (2025). Towards improved fine-mapping of candidate causal variants. Nature Reviews Genetics (advance online publication). PubMed
2023 王 青波. ゲノムワイド関連解析のその先へ：統計的 fine-mapping の基礎と発展. JSBi Bioinformatics Review, 4(1), 35–51. J-STAGE
2018 Schaid, D. J., Chen, W., & Larson, N. B. (2018). From genome-wide associations to candidate causal variants by statistical fine-mapping. Nature Reviews Genetics, 19(8), 491–504. PubMed

Transcriptome-wide association (TWAS)

Year Reference Link
2019 Wainberg, M., Sinnott-Armstrong, N., Mancuso, N., Barbeira, A. N., Knowles, D. A., Golan, D., … & Kundaje, A. (2019). Opportunities and challenges for transcriptome-wide association studies. Nature Genetics, 51(4), 592–599. Journal

Polygenic risk scores

Year Reference Link
2026 Kullo, I. J. (2026). Clinical use of polygenic risk scores: current status, barriers and future directions. Nature Reviews Genetics, 27, 246–263. Journal
2022 Wang, Y., Tsuo, K., Kanai, M., Neale, B. M., & Martin, A. R. (2022). Challenges and opportunities for developing more generalizable polygenic risk scores. Annual Review of Biomedical Data Science, 5, 293–320. Journal
2020 Choi, S. W., Mak, T. S. H., & O'Reilly, P. F. (2020). Tutorial: a guide to performing polygenic risk score analyses. Nature Protocols, 15(9), 2759–2772. PubMed
2019 Martin, A. R., Kanai, M., Kamatani, Y., Okada, Y., Neale, B. M., & Daly, M. J. (2019). Clinical use of current polygenic risk scores may exacerbate health disparities. Nature Genetics, 51(4), 584–591. PubMed

Mendelian randomization

Year Reference Link
2022 Sanderson, E., Glymour, M. M., Holmes, M. V., Kang, H., Morrison, J., Munafò, M. R., … & Davey Smith, G. (2022). Mendelian randomization. Nature Reviews Methods Primers, 2(1), 1–21. Journal

Rare variants

Year Reference Link
2023 Boutry, S., Helaers, R., Lenaerts, T., & Vikkula, M. (2023). Rare variant association on unrelated individuals in case–control studies using aggregation tests: existing methods and current limitations. Briefings in Bioinformatics, 24(6), bbad412. Journal
2015 Auer, P. L., & Lettre, G. (2015). Rare variant association studies: considerations, challenges and opportunities. Genome Medicine, 7(1), 16. PubMed
2014 Lee, S., Abecasis, G. R., Boehnke, M., & Lin, X. (2014). Rare-variant association analysis: study designs and statistical tests. The American Journal of Human Genetics, 95(1), 5–23. PubMed

Genetic architecture

Year Reference Link
2024 Lappalainen, T., Li, Y. I., Ramachandran, S., & Gusev, A. (2024). Genetic and molecular architecture of complex traits. Cell, 187(5), 1059–1075. Journal
2024 Qi, T., Song, L., Guo, Y., Chen, C., & Yang, J. (2024). From genetic associations to genes: methods, applications, and challenges. Trends in Genetics, 40(8), 642–667. Journal
2018 Timpson, N. J., Greenwood, C. M. T., Soranzo, N., Lawson, D. J., & Richards, J. B. (2018). Genetic architecture: the shape of the genetic contribution to human traits and disease. Nature Reviews Genetics, 19(2), 110–124. PubMed

Statistical power

Year Reference Link
2014 Sham, P. C., & Purcell, S. M. (2014). Statistical power and significance testing in large-scale genetic studies. Nature Reviews Genetics, 15(5), 335–346. PubMed

Single-cell genomics

Year Reference Link
2023 Cuomo, A. S. E., Nathan, A., Raychaudhuri, S., MacArthur, D. G., & Powell, J. E. (2023). Single-cell genomics meets human genetics. Nature Reviews Genetics, 24(8), 535–549. Journal

Ancestral diversity

Year Reference Link
2026 Kuchenbaecker, K., & Navoly, G. (2026). Ancestral diversity in complex disease genetics: from discovery to translation. Nature Reviews Genetics. Journal

Useful Websites

Description Link
A Bioinformatician's UNIX Toolbox http://lh3lh3.users.sourceforge.net/biounix.shtml
Osaka university, Department of Statistical Genetics Homepage http://www.sg.med.osaka-u.ac.jp/school_2021.html
Genome analysis wiki (Abecasis Group Wiki) https://genome.sph.umich.edu/wiki/Main_Page
EPI 511, Advanced Population and Medical Genetics
(Alkes Price, Harvard School of Public Health)		 https://alkesgroup.broadinstitute.org/EPI511
fiveMinuteStats
(Matthew Stephens, Statistics and Human Genetics at the University of Chicago)		 https://stephens999.github.io/fiveMinuteStats
Course homepage and digital textbook for Human Genome Variation with Computational Lab https://mccoy-lab.github.io/hgv_modules/

和文

Year Category Reference
2020 遺伝統計学全般 （基礎から発展まで） 実験医学 2020年3月 Vol.38 No.4 GWASで複雑形質を解くぞ! 〜多因子疾患・形質のバイオロジーに挑む次世代のゲノム医科学 単行本 – 2020/2/23 鎌谷 洋一郎 (著)
2020 遺伝統計学全般 （基礎から発展まで） ゼロから実践する 遺伝統計学セミナー〜疾患とゲノムを結びつける 単行本 – 2020/3/13 岡田 随象 (著)
2015 Linux 新しいLinuxの教科書 単行本 – 2015/6/6 三宅 英明 (著), 大角 祐介 (著)
2015 遺伝統計学全般 （基礎から発展まで） 遺伝統計学入門 (岩波オンデマンドブックス) オンデマンド (ペーパーバック) – 2015/12/10 鎌谷 直之 (著)
2012 統計解析（と少し機械学習） データ解析のための統計モデリング入門――一般化線形モデル・階層ベイズモデル・MCMC (確率と情報の科学) 単行本 – 2012/5/19 久保 拓弥 (著)
2012 統計解析（と少し機械学習） はじめてのパターン認識 単行本（ソフトカバー） – 2012/7/31 平井 有三 (著)
1992 統計解析（と少し機械学習） 自然科学の統計学 (基礎統計学) 単行本 – 1992/8/1 東京大学教養学部統計学教室 (編集)
1991 統計解析（と少し機械学習） 統計学入門 (基礎統計学Ⅰ) 単行本 – 1991/7/9 東京大学教養学部統計学教室 (編集)
~ 遺伝統計学全般 （基礎から発展まで） 遺伝子医学 シリーズ企画 Statistical Genetics　〈遺伝統計学の基礎〉 - 鎌谷 洋一郎 + α