MODAS (Multi-Omics Data Association Study toolkit) is an efficient software for high-dimensional omics data association analysis. A major feature of MODAS is its novel genome-wide association analysis (GWAS) strategy for high-dimensional omics data. Firstly, MODAS generates pseudo-genotype files to reduce the dimensionality of the original SNP-based genotype data; then, it performs block-based GWAS to screen out the significantly associated genomic regions (SAGRs); finally, it performs SNP-based association analysis on the SAGRs to obtain the QTLs for the high-dimensional omics data. Another feature of MODAS is that it introduces Mendelian randomization algorithm to infer the genetic regulation relationship between omics-data related QTLs, which helps biological hypothesis establishment. Moreover, a HTML based web page is implemented in MODAS for the visualization and query of omics-data based GWAS results, which facilitate further gene function mining.
MODAS was developed by Songyu Liu in 2021.
Please read the tutorial for details!