To access the NTA Study Reporting Tool (SRT) as a stand-alone tool for evaluating and scoring reporting, see: NTA Study Reporting Tool
The links in the table below, which follows the same structure as the stand-alone SRT, connect to reference content about each topic. The content is organized according to the chronology of a typical NTA study. For each section, you will find text distilled from relevant literature to describe current, published NTA practices. In addition, recommendations regarding good practices for performing and reporting NTA research are offered.
| Section | Category | Sub-Category | Example Information |
|---|---|---|---|
| Methods | Study Design | Objectives & Scope | • Study goals and hypotheses • Scope of the study with respect to use of NTA / suspect screening • Expected chemical coverage of approach and potential limitations |
| Sample Information & Preparation | • Sample collection/replication, handling/storage, preparation, extraction, & clean-up methods (and related QA practices) • Intended use of samples (e.g., method development, compound identification, etc.) • Development and intended use of blanks |
||
| QC Spikes & Samples | • Development of QC spikes/samples (e.g., isotopically labeled standards/spikes, native standard spikes, matrix pools) • Intended use of QC spikes/samples (e.g., to monitor instrument performance, data normalization, etc.) |
||
| Data Acquisition | Analytical Sequence | • Sample randomization and use of replicate injections • Inclusion of blanks and QC samples in the acquisition sequence • Information about single vs. multiple analytical batches |
|
| Chromatography | • Instrument specifications • Method settings (e.g., column/guard, mobile phases, gradient, injection techniques) |
||
| Mass Spectrometry | • Instrument specifications • Instrument calibration and/or tuning procedures • Method settings (e.g., acquisition parameters, such as polarity, resolution, data-dependent vs. data-independent) |
||
| Data Processing & Analysis | Data Processing | • File conversion information (e.g., to open-source format, centroiding) • Software program(s) used • Workflow steps (e.g., peak picking, RT calibration, alignment, gap filling) and settings • Feature detection thresholds (e.g., replicate detection criteria; min height, area, or S/N levels; comparison to occurrence/abundance in blanks) • Data correction or normalization methods (e.g., peak area/height normalization or scaling, blank subtraction) |
|
| Statistical & Chemometric Analysis | • Software programs(s)/package(s) used & samples/sample groups to which analyses were applied • Basic statistical analysis method goals (e.g., summarize data, evaluate variability, hypothesis testing), type (e.g., Wilcoxon rank sum test, Chi-square test), assumptions, and settings/thresholds • Chemometric analysis method goals (e.g., prioritize features, compare/classify samples, evaluate relationships between features), type (e.g., differential analysis, hierarchical clustering, dimensionality reduction), assumptions, and settings/thresholds |
||
| Annotation & Identification | • Software program(s) used (or description of manual annotation/identification efforts) • Libraries and databases used (including details such as chemical coverage, resolution, metadata inclusion; information about in-house databases) • Workflow steps (e.g., formula assignment, suspect screening, MS/MS spectral interpretation or library matching) • Workflow methods & settings (e.g., formula prediction method, scoring algorithms; mass error/RT tolerances, accepted match scores) |
||
| Results | Data Outputs | Statistical & Chemometric Outputs | • Basic statistical outputs (e.g., adj. p-values, standard deviations, test statistics) • Results of chemometric analyses (e.g., reported classifications/groupings of features or samples, observed trends in the data) • Visuals/plots (e.g., Venn diagrams, heatmaps, clustering dendrograms, volcano plots, network diagrams, PCA and loading plots) • New statistical metrics, algorithms, packages, and/or scripts |
| Identification & Confidence Levels | • Reported identifications and associated confidence levels (e.g., levels described by Schymanski et al.) • Supporting data for annotation/identification (e.g., formula match scores, fine isotope pattern, retention time match, MS/MS match scores, source of MS/MS spectra) • For features with lower confidence IDs, (i.e., not standard-confirmed), proposed tentative structures and other annotated data • Semi-quantification or quantification data • Exported MS/MS spectra (e.g., as a library, database, or deposition into online repository) |
||
| QA/QC Metrics | Data Acquisition QA/QC | • Quality: Adherence to QA/QC protocols for sample preparation and data acquisition • Boundary: Description of the potential impacts of methods (sample prep, chromatographic, MS) on observable chemical space • Accuracy: Reported chromatographic and mass accuracy • Precision: Variability of observed retention time, precursor mass error, and abundance |
|
| Data Processing & Analysis QA/QC | • Quality: Outcomes of QC checks along the data processing & analysis workflow • Boundary: Impact of data processing & analysis method(s) on observed chemical space, observed limits of detection/ID • Accuracy: Performance measures (True Positive Rate, False Positive Rate, etc.) for known compounds or samples with known classification • Precision: Reproducibility/repeatability of performance measures for known compounds or samples with known classification; Calculations such as False Discovery Rate, F1 score, etc. |
Click here for a list of acronyms used in the Reference Content