# Description of contents ## Meta-analyzed placental mQTL All mQTL meta-analyzed as outlined in Casazza et al[^1] are located within `meta-analyzed-mqtl`, and labeled by their corresponding mQTL category. They are stored in the MeCs[^2] plain text format outlined on [their wiki](https://yanglab.westlake.edu.cn/software/smr/#MeCS). Code used in generating this data, in addition to several analyses discussing potential function of these mQTL and their role in complex traits, can be found at https://github.com/wilcas/sex_specific_mQTL. Files that are larger than 5GB (OSF's file size limit) were split using the Unix `split` utility into parts and can be combined using the following syntax: `cat FILENAME.parta* > FILENAME` `sldsc_annotations.tar.gz` Contains Maximum Causal Posterior Probabiltiy (maxCPP) and 95% Credible Set stratified linkage disequilibrium score regression ([S-LDSC](https://github.com/bulik/ldsc/wiki/Partitioned-Heritability)[^3] annotations, derived using CAVIAR[^4] on all SNPs within 75kb of a CpG site with at least one mQTL association at an FDR < 0.05. [^1] Manuscript in preparation [^2] Qi T, Wu Y, Zeng J, Zhang F, Xue A, Jiang L, Zhu Z, Kemper K, Yengo L, Zheng Z, eQTLGen Consortium, Marioni RE, Montgomery GW, Deary IJ, Wray NR, Visscher PM, McRae AF & Yang J (2018) Identifying gene targets for brain-related traits using transcriptomic and methylomic data from blood. Nature Communications, 9: 2282. [^3]Finucane HK, Bulik-Sullivan B, Gusev A, Trynka G, Reshef Y, Loh PR, et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nature genetics. 2015 Nov;47(11):1228–35. [^4] Hormozdiari F, Kostem E, Kang EY, Pasaniuc B, Eskin E. Identifying Causal Variants at Loci with Multiple Signals of Association. Genetics. 2014 Oct;198(2):497–508.