MIRTH: Metabolite Imputation via Rank-Transformation and Harmonization Journal Article
| Authors: | Freeman, B. A.; Jaro, S.; Park, T.; Keene, S.; Tansey, W.; Reznik, E. |
| Article Title: | MIRTH: Metabolite Imputation via Rank-Transformation and Harmonization |
| Abstract: | Out of the thousands of metabolites in a given specimen, most metabolomics experiments measure only hundreds, with poor overlap across experimental platforms. Here, we describe Metabolite Imputation via Rank-Transformation and Harmonization (MIRTH), a method to impute unmeasured metabolite abundances by jointly modeling metabolite covariation across datasets which have heterogeneous coverage of metabolite features. MIRTH successfully recovers masked metabolite abundances both within single datasets and across multiple, independently-profiled datasets. MIRTH demonstrates that latent information about otherwise unmeasured metabolites is embedded within existing metabolomics data, and can be used to generate novel hypotheses and simplify existing metabolomic workflows. © 2022, The Author(s). |
| Keywords: | research design; methodology; metabolomics; imputation; procedures; workflow; missing data; article; matrix factorization; unmeasured metabolites |
| Journal Title: | Genome Biology |
| Volume: | 23 |
| ISSN: | 1465-6906 |
| Publisher: | Biomed Central Ltd |
| Date Published: | 2022-09-01 |
| Start Page: | 184 |
| Language: | English |
| DOI: | 10.1186/s13059-022-02738-3 |
| PUBMED: | 36050754 |
| PROVIDER: | scopus |
| PMCID: | PMC9438248 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 3 October 2022 -- Source: Scopus |
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