Extended Data Fig. 4: sQTL power, sharing, and sex-biases.

(a) The inverse relationship between the mean absolute effect size of cis-sQTLs (y-axis) and the number of donors (x-axis) across 19 cell types (Pearson’s r = -0.95). Each black dot represents one cell type. The dark blue line represents the fitted linear regression model, and the grey shadow represents the 95% confidence interval in the linear regression. (b) The positive relationship between the number of sGenes and the total junction read counts across 19 cell types (Pearson’s r = 0.96). Each black point represents one cell type. The shaded area represents 95% confidence interval. (c) Fractions of cell-type-specific sQTLs detected by mashr using a threshold of LFSR < 0.05 shared by various numbers of cell types. LFSR = local false sign rate. (d) An example of single-sex sQTLs (rs930090 modulated TECR intron chr19:14529711-14562525; N = 459). The allelic effect in CD16⁺ NK was only significant in females but not males. (e) An example of sex-differential sQTLs (rs17713729 modulated SH3YL1 intron chr2: 253115-264782; N = 459). The allelic effect in cm CD4⁺ T was significant in both males and females but larger in males than in females. (f) An example of Malay-specific sQTLs (rs492083 modulated ATP5MPL intron chr14: 103914633-103915066; N = 456). The allelic effect in CD16+ Monocyte was significant in Malay but not significant in East Asian. (g) An example of Indian-specific sQTLs (rs6576010 modulated POLB intron chr8: 42338685-42344953; N = 458). The allelic effect in Naive CD4⁺ T was significant in Indian but not significant in East Asian. Note: The box plots show median and interquartile range (IQR), and whiskers are 1.5-fold IQR in (d), (e), (f) and (g). Unadjusted two-sided P value was calculated by QTLtools in (d), (e), (f) and (g). Red lines in (d), (e), (f) and (g) indicate significant linear relationship between intron usage and genotype.