# Metabolite Stability Assessment Across Cohorts > Use when you have uploaded a pre-analytical data table containing sample metadata, processing timestamps (pre- and post-centrifugation), and NMR metabolomic measurements for a cohort of peripheral blood samples (plasma/serum), and you need to quantify the magnitude and direction of metabolite. - Skill: `holobiomicslab/metabolite-stability-assessment-across-cohorts-2` (Agent Skill) - Install (CLI): `npx skillmds@latest add holobiomicslab/metabolite-stability-assessment-across-cohorts-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/holobiomicslab/metabolite-stability-assessment-across-cohorts-2/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Data & Analytics - License: CC-BY-4.0 - Author: HolobiomicsLab (https://skillmd.com/u/holobiomicslab) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/holobiomicslab/metabolite-stability-assessment-across-cohorts-2 --- # metabolite-stability-assessment-across-cohorts > **License: restricted** — no clear open-source license detected for the underlying tool; verify licensing before commercial use or redistribution. ## Summary Quantify how pre- and post-centrifugation processing delays affect metabolite concentrations and data quality across a sample cohort using NMR metabolomic measurements. This skill produces stratified performance reports that identify which metabolites are stable or degraded over defined delay windows, enabling prioritization of processing protocols. ## When to use You have uploaded a pre-analytical data table containing sample metadata, processing timestamps (pre- and post-centrifugation), and NMR metabolomic measurements for a cohort of peripheral blood samples (plasma/serum), and you need to quantify the magnitude and direction of metabolite concentration shifts and data quality loss as a function of processing delay to assess cohort-level stability and generate actionable performance thresholds. ## When NOT to use - Input data lacks paired pre- and post-centrifugation timestamps or SPREC delay classification — the skill requires explicit delay stratification to compute meaningful comparisons. - Samples are from tissue or non-blood matrices — the tool is calibrated for peripheral blood (plasma/serum) pre-analytical effects and may not generalize. - No reference time-point or minimal-delay control is available — the skill compares metabolite shifts relative to a baseline delay state; absence of this anchor undermines relative change calculation. ## Inputs - Pre-analytical data table (tabular format: .csv, .xlsx, or similar) containing sample identifiers, pre-centrifugation delay (minutes), post-centrifugation delay (minutes), and NMR metabolomic measurements (metabolite names and concentration values) ## Outputs - Performance report artifact (HTML or CSV table) with delay-stratified metabolite changes, cohort-level statistics (mean, variance by delay bin), data quality indicators, and color-coded stability flags (minor/major change thresholds) - Interactive visualization dashboard (lollipop plots or alternative representations) showing metabolite stability across time-points by SPREC classification or custom delay grouping ## How to apply Load the pre-analytical data table into PRIMA-Panel and parse the required fields: sample identifiers, pre- and post-centrifugation delay timestamps (converted to minutes), and corresponding NMR metabolomic measurements. Stratify the cohort by delay intervals (e.g., using SPREC classification or user-defined time-points). For each metabolite, calculate the absolute and relative concentration shift (% change) between the reference (minimal delay) and each delay stratum. Adjust minor and major change % thresholds according to your stability acceptance criteria (default thresholds provided in the tool). Generate a performance report table highlighting metabolites exceeding the major threshold for each delay window, with associated data quality indicators. Color-code entries to visualize stability patterns and export as HTML report or CSV for downstream visualization and threshold justification. ## Related tools - **PRIMA-Panel** (Interactive data exploration and performance report generation for processing delay effects on metabolite stability; accepts pre-analytical metadata and NMR measurements, computes cohort-level delay-stratified metabolite shifts, and exports structured performance artifacts) — https://github.com/funkam/PRIMA - **QC-Tool** (Quality control and pre-analytical data validation; supports timestamp parsing and SPREC classification) — https://github.com/funkam/QC-Tool ## Evaluation signals - Output report contains all metabolites from the input table, with no missing or silently dropped entries; row and column counts match expected dimensions. - Calculated % changes are directionally consistent with known metabolite stability biology (e.g., glucose and amino acids typically degrade over time; lipids may shift in predictable directions). - Minor and major change thresholds are applied consistently across all delay strata; metabolites flagged as 'major change' exceed the user-specified % threshold in the corresponding delay bin. - Cohort-level statistics (mean, SD, count by delay stratum) are internally consistent; counts sum to total sample size, and mean shifts are monotonic or show plausible non-monotonic patterns across increasing delay windows. - Report can be successfully exported in HTML and CSV formats without data truncation or encoding errors; downstream visualization tools ingest the structured output without schema violations. ## Limitations - The tool is optimized for peripheral blood (plasma/serum) samples; applicability to other matrices (cerebrospinal fluid, urine, tissue) is not validated. - Performance thresholds (minor/major % change cutoffs) are user-adjustable but lack evidence-based guidance; practitioners must calibrate thresholds against their own stability acceptance criteria or existing literature standards. - The skill assumes linear or piecewise-linear metabolite degradation over the observed delay range; non-linear or biphasic stability profiles may not be detected without binning strategy adjustment. - NMR measurement noise and instrument drift are not explicitly modeled; data quality indicators reflect cohort-level variability but do not deconvolve pre-analytical effects from instrumental variation. - Requires complete or near-complete metadata (timestamps, metabolite IDs); missing data in delay fields or sparse metabolite coverage will reduce report interpretability and cohort representativeness. ## Evidence - [other] Workflow step 1: Load pre-analytical data table: "Load the pre-analytical data table (containing sample metadata, processing delay information, and NMR metabolomic measurements) into PRIMA-Panel." - [other] Workflow step 3: Calculate performance metrics: "Calculate performance metrics quantifying the effect of processing delays on metabolic parameters (e.g., metabolite concentration shifts, data quality degradation) across the sample cohort." - [intro] Core functionality: Tool investigates processing delay effects: "The PRIMA-Panel is a tool to investigate the effect of processing delays on metabolic parameters in samples of peripheral blood (plasma / serum)." - [readme] Data module: Delay-stratified visualization: "The Data tab shows different ways of highlighting the different stability time-points in minutes. The time-points are sorted according to their SPREC classification." - [readme] Performance report module: Threshold-based metabolite change detection: "A table is then generated that higlights a minor and a major change for each metabolite in that given timeframe. The colors, as well as the % threshholds, can be adjusted." - [readme] Output artifact: Exportable structured report: "The table can be downloaded as a .HTML report or the table directly as .csv (or other formats)."