mzTab-M: A Data Standard for Sharing Quantitative Results in Mass Spectrometry Metabolomics

Abstract

Mass spectrometry (MS) is one of the primary techniques used for large-scale analysis of small molecules in metabolomics studies. To date, there has been little data format standardization in this field, as different software packages export results in different formats represented in XML or plain text, making data sharing, database deposition, and reanalysis highly challenging. Working within the consortia of the Metabolomics Standards Initiative, Proteomics Standards Initiative, and the Metabolomics Society, we have created mzTab-M to act as a common output format from analytical approaches using MS on small molecules. The format has been developed over several years, with input from a wide range of stakeholders. mzTab-M is a simple tab-separated text format, but importantly, the structure is highly standardized through the design of a detailed specification document, tightly coupled to validation software, and a mandatory controlled vocabulary of terms to populate it. The format is able to represent final quantification values from analyses, as well as the evidence trail in terms of features measured directly from MS (e.g., LC-MS, GC-MS, DIMS, etc.) and different types of approaches used to identify molecules. mzTab-M allows for ambiguity in the identification of molecules to be communicated clearly to readers of the files (both people and software). There are several implementations of the format available, and we anticipate widespread adoption in the field.

Figure 1

Overall structure of an mzTab-M file. (A) Metadata about the experiment, describing experimental design (study variables and assays), links to other files, etc.. (B) The small molecule (SML) table, capturing “final” results table: i.e., overall calculated quantification value (and identity where known) of a metabolite. (C) Quantification value in each (aligned) MS run for MS¹ features: e.g., mapped to individual adducts or charge states of a molecule. (D) Evidence supporting identification (with ambiguity if needed) for molecules, using CV terms for scores/statistics where available.

Figure 2

Simple experimental designs in mzTab-M can be represented using a combination of the elements study_variable (SV), assay, ms_run, and sample. Quantitative values can be reported in files for SVs and assays. (A) SV is intended to capture different groups of replicates, which might have resulted from different levels of a given variable: e.g. control versus treated (represented as 2 SVs) and n time points over a treatment course (as n SVs). (B) assay captures a measurement made about a molecule (small molecule/lipid) where multiple assays within the same SV are taken to be replicates of some kind (biological or technical). (C) ms_run captures a single run on an MS instrument. (D) Samples are optional in mzTab, since the quantitative software may often be unaware of the biological samples that have been analyzed. If that information is available, references from assay to the same (technical, upper half) or different (biological, bottom half) samples are used to describe the type of replication performed.

Figure 3

(A) The summary level (SML) reports the final assumed identifications, allowing for ambiguity by including “|” separated results in the relevant columns. (B) The feature level (SMF) does not explicitly report identifications but references down to the SME level. Ambiguity is propagated via referencing multiple SME rows with different identification results. (C) One SME row represents a single possible identification from some input evidence. Multiple identifications from the same input data share the same value for evidence_input_id. Ambiguity can be captured by different rows for the same input data.