. 2020 Dec 16;36(22-23):5424–5431. doi: 10.1093/bioinformatics/btaa1029

Table 2.

Summary of external GWAS summary statistics used

Trait	GWAS citation	GWAS sample size	No. of GWAS variants	No. of matched variants	Mean $χ^{2}$	No. of hits	No. of indep hits
Breast cancer (BRCA)	Michailidou et al. (2017)	137 045/119 078	11 792 542	1 114 424	1.70	2941	157
Rheumatoid arthritis (RA)	Okada et al. (2014)	29 880/73 758	9 739 303	656 087	2.10	3663	75
Type 1 diabetes (T1D)	Censin et al. (2017)	5913/8828	8 996 866	514 420	1.93	1902	39
Type 2 diabetes (T2D)	Scott et al. (2017)	26 676/132 532	12 056 346	1 108 760	1.24	388	39
Prostate cancer (PRCA)	Schumacher et al. (2018)	79 148/61 106	20 370 946	1 115 688	1.55	2762	137
Depression (MDD)	Wray et al. (2018)	59 851/113 154	13 554 550	1 103 440	1.27	166	5
Coronary artery disease (CAD)	Nikpay et al. (2015)	60 801/123 504	9 455 778	1 108 313	1.13	352	37
Asthma	Demenais et al. (2018)	19 954/107 715	2 001 280	980 430	1.10	365	15

Note: The GWAS sample size is the number of cases/controls in the GWAS. The mean chi-squared statistics $χ^{2}$ and the number of hits ( $P < 5 \cdot 10^{- 8}$ ) are reported after restricting to HapMap3 variants and matching with the UKBB data. Independent hits are the hits remaining after clumping at $r^{2} > 0.01$ within 10 Mbp.