# Chemodiversity Descriptor Calculation > Use when you have a formula-assigned FT-ICR MS dataset (CSV or tab-delimited table with molecular formulas and mass values) and need to quantify the molecular chemodiversity, elemental composition diversity, or complexity of environmental organic samples for cross-sample comparison or. - Skill: `holobiomicslab/chemodiversity-descriptor-calculation` (Agent Skill) - Install (CLI): `npx skillmds@latest add holobiomicslab/chemodiversity-descriptor-calculation` - Raw SKILL.md: https://api.skillmd.com/api/skills/holobiomicslab/chemodiversity-descriptor-calculation/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/chemodiversity-descriptor-calculation --- # chemodiversity-descriptor-calculation ## Summary Compute molecular chemodiversity descriptors (mass-based statistics, elemental stoichiometry diversity indices, and molecular complexity metrics) from formula-assigned FT-ICR MS datasets to characterize the molecular diversity and transformation patterns of environmental organic complex mixtures. ## When to use Apply this skill when you have a formula-assigned FT-ICR MS dataset (CSV or tab-delimited table with molecular formulas and mass values) and need to quantify the molecular chemodiversity, elemental composition diversity, or complexity of environmental organic samples for cross-sample comparison or transformation analysis. ## When NOT to use - Input is not formula-assigned: MoleTrans requires parsed molecular formulas; raw m/z values without formula assignment cannot be processed. - Data source is not FT-ICR MS or supported mass spectrometry: while MoleTrans can partially support compound-annotated results from other MS approaches, it is optimized for FT-ICR formula assignments. - Sample lacks sufficient molecular diversity: descriptor computation assumes a heterogeneous molecular population; homogeneous or single-compound samples may not benefit from chemodiversity metrics. ## Inputs - formula-assigned FT-ICR MS dataset (CSV or tab-delimited table) - columns: molecular formulas, mass values, sample identifiers ## Outputs - structured descriptor table with sample identifiers and chemodiversity metrics - mass-based statistics per sample - elemental stoichiometry diversity indices per sample - molecular complexity metrics per sample ## How to apply Load the formula-assigned FT-ICR MS dataset into MoleTrans post-analysis module. Parse the molecular formula assignments to extract elemental composition (C, H, O, N, S, P counts) for each formula. Compute a suite of chemodiversity descriptors including mass-based statistics (e.g., mean, median, standard deviation of molecular masses), elemental stoichiometry diversity indices (ratios and proportional distributions of elements), and molecular complexity metrics across the sample. Export a structured output table or report mapping sample identifiers to descriptor values. Validate that computed indices capture expected trends in molecular complexity and that elemental counts match the input formulas. ## Related tools - **MoleTrans** (post-analysis and data-mining platform for computing chemodiversity descriptors from formula-assigned FT-ICR MS datasets) — github.com/JibaoLiu/MoleTrans ## Evaluation signals - Output descriptor table contains one row per sample with all expected chemodiversity metrics (mass statistics, elemental diversity indices, complexity scores) populated and non-null. - Elemental composition counts (C, H, O, N, S, P) in parsed formulas match the elemental tallies reflected in stoichiometry diversity indices. - Molecular complexity metrics show expected correlation with formula mass and elemental richness (e.g., higher complexity for larger, more heteroatom-rich molecules). - Sample identifiers in output table map one-to-one to input dataset rows; no duplicates or drops. - Descriptor values fall within chemically plausible ranges (e.g., mass > 0, diversity indices 0–1 or within documented scale). ## Limitations - MoleTrans can only partially support combined analysis on compound-annotated results from non-FT-ICR MS approaches; full optimization is for FT-ICR formula-assigned data. - Requires user registration (or demo account) to access the live webtool; source code from the repository provides only the main calculation functions and algorithms, not the complete web interface. - Descriptor computation assumes adequate sample size and molecular diversity; very small or homogeneous datasets may yield uninformative or unreliable indices. - Post-analysis is limited to elemental composition (C, H, O, N, S, P); other elements present in formulas may not be represented in standard diversity metrics. ## Evidence - [other] formula-assigned FT-ICR MS dataset (CSV or tab-delimited table with molecular formulas and mass values): "Load the formula-assigned FT-ICR MS dataset (CSV or tab-delimited table with molecular formulas and mass values) into the MoleTrans post-analysis module" - [other] chemodiversity descriptors including mass-based statistics, elemental stoichiometry diversity indices, and molecular complexity metrics: "Compute molecular chemodiversity descriptors including mass-based statistics, elemental stoichiometry diversity indices, and molecular complexity metrics across the sample." - [readme] MoleTrans is a webtool for post analysis and data mining on the formula assigned datasets from FT-ICR MS: "MoleTrans is a webtool for post analysis and data mining on the formula assigned datasets from FT-ICR MS." - [readme] it can partialy support the combined analysis on the compound annotated results based on other mass spectrometry: "Alternatively, it can partialy support the combined analysis on the compound annotated results based on other mass spectrometry." - [other] Extract elemental composition (C, H, O, N, S, P counts): "Parse the molecular formula assignments and extract elemental composition (C, H, O, N, S, P counts)."