这两个软件我算都比较熟悉了,SMR最早是做GWAS那会儿, 用GCTA的时候见到的。就挂在Yang LabSoftware | Yang Lab (westlake.edu.cn)的首页,想不关注也很难。 但我个人开发的MR流程和数据储备一直都以TSMR包为主。一直没觉得有什么问题,毕竟MR的核心就是个比值,还能有多大差别。但本真科学严谨的态度,还是求证...
在选择QTL孟德尔随机化方法时，两个软件：SMR与TSMR，引发了关注。SMR最早于GWAS研究期间，通过GCTA工具被提出，并主要集中在计算基因表达水平与性状之间的多效性。此算法旨在评估单核苷酸多态性（SNP）对表型影响的中介作用是否通过基因表达水平实现，进一步为GWAS获得的疾病相关基因提供优先级排序。此方法已...
head(f) fwrite(fwrite.table(gsmr_data[,c(1,2)], "gsmr_example_snps.allele", col.names=F, row.names=F, quote=F), "GWAS_formatted_for_GCTA.txt", sep = "\t", quote = F, na = "NA", dec = ".")编辑于 2024-05-14 22:21・IP 属地美国 ...
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--gwas-summary reads summary-level data from GWAS. The input format follows that for GCTA-COJO analysis (http://cnsgenomics.com/software/gcta/#COJO). --mbfile reads a text file with each row representing a PLINK binary file (e.g., one for each chromosome) from a reference sample for ...
<<endl; fclose(logfile); } void make_besd(char*outFileName, char* syllabusName, bool gctaflag,bool plinkflag,bool gemmaflag,bool merlinflag,bool boltflag, bool save_dense_flag,int cis_itvl, int trans_itvl, float transThres, float restThres,bool samegeno, int addn) { if(samegeno) {...