From differential abundance to mtGWAS: accurate and scalable methodology for metabolomics data with non-ignorable missing observations and latent factors
从差异丰度到代谢物全基因组关联:非可忽略缺失与潜在因子下的方法
Metabolomics is the high-throughput study of small molecule metabolites. Besides offering novel biological insights, these data contain unique statistical challenges, the most glaring of which is the many non-ignorable missing metabolite observations. To address this issue, nearly all analysis pipelines first impute missing observations, and subsequently perform analyses with methods designed for complete data. While clearly erroneous, these pipelines provide key practical…