molecular-complexity-metric-computation
Summary
Compute molecular complexity metrics and chemodiversity descriptors from formula-assigned FT-ICR MS datasets to quantify the structural and compositional diversity of environmental organic complex mixtures. This enables systematic characterization of molecular transformations and reactivity patterns across environmental samples.
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 structural diversity, elemental stoichiometry patterns, or complexity landscape of the organic mixture. Typical triggers include: exploring chemodiversity across treatment conditions, comparing DOM reactivity in anaerobic systems, or screening for molecular transformation patterns in environmental samples.
When NOT to use
- Input dataset lacks molecular formula assignments or contains only m/z values without elemental composition—use formula assignment/annotation tools first.
- Data are already pre-aggregated into a feature or descriptor table—this skill is for raw formula-to-metric transformation, not re-computation.
- Sample size is <2 or dataset is a single chromatographic peak—complexity metrics are most meaningful at the mixture level, not individual compound level.
Inputs
- Formula-assigned FT-ICR MS dataset in CSV or tab-delimited format with columns: molecular formula, mass (m/z), sample identifier
- Elemental composition counts extracted from parsed molecular formulas
Outputs
- Structured descriptor table with rows = samples, columns = computed complexity and chemodiversity metrics (mass-based statistics, elemental ratios, diversity indices, molecular complexity scores)
- Sample-level summary report with descriptor values and sample identifiers
How to apply
Load the formula-assigned FT-ICR MS dataset into the MoleTrans post-analysis module. Parse molecular formula assignments to extract elemental composition counts (C, H, O, N, S, P). Compute mass-based statistics (e.g., mean mass, mass range), elemental stoichiometry diversity indices (e.g., H/C, O/C ratios), and molecular complexity metrics (e.g., degree of unsaturation, aromaticity indices) across the sample. Generate and export a structured output table containing computed descriptors indexed by sample identifier. Evaluate correctness by verifying that descriptor ranges are chemically plausible (e.g., H/C 0–2.5, O/C 0–1.2 for natural organic matter) and that sample-level statistics are consistent with the input formula cardinality.
Related tools
- MoleTrans (Webtool for post-analysis and data mining on formula-assigned FT-ICR MS datasets; computes molecular chemodiversity descriptors and complexity metrics.) — https://github.com/JibaoLiu/MoleTrans
Evaluation signals
- Elemental composition counts (C, H, O, N, S, P) are non-negative integers consistent with parsed molecular formulas.
- Computed descriptors fall within chemically plausible ranges for environmental organic matter (H/C 0–2.5, O/C 0–1.2, mass typically 200–1000 Da).
- Sample-level descriptor values are consistent with the cardinality and composition of the input formula set (no NaN or infinite values for valid inputs).
- Output table schema matches the declared format (sample ID, descriptor name, descriptor value, units) with no missing values for complete input records.
- Descriptor variance across samples is non-zero and correlates with known treatment or transformation conditions (e.g., higher O/C in oxidized samples, higher aromaticity in aged DOM).
Limitations
- MoleTrans partially supports formula-assigned datasets from FT-ICR MS; combined analysis on compound-annotated results from other mass spectrometry approaches has reduced coverage.
- Molecular complexity metrics are aggregate descriptors and do not resolve individual compound-level reactivity or transformation pathways.
- Accuracy of computed metrics depends on quality and completeness of upstream formula assignment; systematic mass calibration or formula assignment errors will propagate to descriptor values.
- The skill does not provide statistical significance testing or hypothesis-driven filtering; practitioner must post-process descriptor output for comparative or correlation analysis.
Evidence
- [other] MoleTrans ingests formula-assigned datasets from FT-ICR MS and performs post-analysis and data mining operations to enable molecular chemodiversity exploration and transformation analysis of environmental organic complex mixtures.: "MoleTrans ingests formula-assigned datasets from FT-ICR MS and performs post-analysis and data mining operations to enable molecular chemodiversity exploration and transformation analysis of"
- [other] 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 from the published source code repository.: "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 from the published source code repository"
- [other] Parse the molecular formula assignments and extract elemental composition (C, H, O, N, S, P counts). Compute molecular chemodiversity descriptors including mass-based statistics, elemental stoichiometry diversity indices, and molecular complexity metrics across the sample.: "Parse the molecular formula assignments and extract elemental composition (C, H, O, N, S, P counts). Compute molecular chemodiversity descriptors including mass-based statistics, elemental"
- [readme] MoleTrans is a webtool for post analysis and data mining on the formula assigned datasets from FT-ICR MS. Alternatively, it can partialy support the combined analysis on the compound annotated results based on other mass spectrometry.: "MoleTrans is a webtool for post analysis and data mining on the formula assigned datasets from FT-ICR MS. Alternatively, it can partialy support the combined analysis on the compound annotated"
1---2name: molecular-complexity-metric-computation-23description: 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 structural diversity, elemental stoichiometry patterns, or complexity landscape of the organic mixture.4license: CC-BY-4.05---67# molecular-complexity-metric-computation89## Summary1011Compute molecular complexity metrics and chemodiversity descriptors from formula-assigned FT-ICR MS datasets to quantify the structural and compositional diversity of environmental organic complex mixtures. This enables systematic characterization of molecular transformations and reactivity patterns across environmental samples.1213## When to use1415Apply 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 structural diversity, elemental stoichiometry patterns, or complexity landscape of the organic mixture. Typical triggers include: exploring chemodiversity across treatment conditions, comparing DOM reactivity in anaerobic systems, or screening for molecular transformation patterns in environmental samples.1617## When NOT to use1819- Input dataset lacks molecular formula assignments or contains only m/z values without elemental composition—use formula assignment/annotation tools first.20- Data are already pre-aggregated into a feature or descriptor table—this skill is for raw formula-to-metric transformation, not re-computation.21- Sample size is <2 or dataset is a single chromatographic peak—complexity metrics are most meaningful at the mixture level, not individual compound level.2223## Inputs2425- Formula-assigned FT-ICR MS dataset in CSV or tab-delimited format with columns: molecular formula, mass (m/z), sample identifier26- Elemental composition counts extracted from parsed molecular formulas2728## Outputs2930- Structured descriptor table with rows = samples, columns = computed complexity and chemodiversity metrics (mass-based statistics, elemental ratios, diversity indices, molecular complexity scores)31- Sample-level summary report with descriptor values and sample identifiers3233## How to apply3435Load the formula-assigned FT-ICR MS dataset into the MoleTrans post-analysis module. Parse molecular formula assignments to extract elemental composition counts (C, H, O, N, S, P). Compute mass-based statistics (e.g., mean mass, mass range), elemental stoichiometry diversity indices (e.g., H/C, O/C ratios), and molecular complexity metrics (e.g., degree of unsaturation, aromaticity indices) across the sample. Generate and export a structured output table containing computed descriptors indexed by sample identifier. Evaluate correctness by verifying that descriptor ranges are chemically plausible (e.g., H/C 0–2.5, O/C 0–1.2 for natural organic matter) and that sample-level statistics are consistent with the input formula cardinality.3637## Related tools3839- **MoleTrans** (Webtool for post-analysis and data mining on formula-assigned FT-ICR MS datasets; computes molecular chemodiversity descriptors and complexity metrics.) — https://github.com/JibaoLiu/MoleTrans4041## Evaluation signals4243- Elemental composition counts (C, H, O, N, S, P) are non-negative integers consistent with parsed molecular formulas.44- Computed descriptors fall within chemically plausible ranges for environmental organic matter (H/C 0–2.5, O/C 0–1.2, mass typically 200–1000 Da).45- Sample-level descriptor values are consistent with the cardinality and composition of the input formula set (no NaN or infinite values for valid inputs).46- Output table schema matches the declared format (sample ID, descriptor name, descriptor value, units) with no missing values for complete input records.47- Descriptor variance across samples is non-zero and correlates with known treatment or transformation conditions (e.g., higher O/C in oxidized samples, higher aromaticity in aged DOM).4849## Limitations5051- MoleTrans partially supports formula-assigned datasets from FT-ICR MS; combined analysis on compound-annotated results from other mass spectrometry approaches has reduced coverage.52- Molecular complexity metrics are aggregate descriptors and do not resolve individual compound-level reactivity or transformation pathways.53- Accuracy of computed metrics depends on quality and completeness of upstream formula assignment; systematic mass calibration or formula assignment errors will propagate to descriptor values.54- The skill does not provide statistical significance testing or hypothesis-driven filtering; practitioner must post-process descriptor output for comparative or correlation analysis.5556## Evidence5758- [other] MoleTrans ingests formula-assigned datasets from FT-ICR MS and performs post-analysis and data mining operations to enable molecular chemodiversity exploration and transformation analysis of environmental organic complex mixtures.: "MoleTrans ingests formula-assigned datasets from FT-ICR MS and performs post-analysis and data mining operations to enable molecular chemodiversity exploration and transformation analysis of"59- [other] 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 from the published source code repository.: "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 from the published source code repository"60- [other] Parse the molecular formula assignments and extract elemental composition (C, H, O, N, S, P counts). Compute molecular chemodiversity descriptors including mass-based statistics, elemental stoichiometry diversity indices, and molecular complexity metrics across the sample.: "Parse the molecular formula assignments and extract elemental composition (C, H, O, N, S, P counts). Compute molecular chemodiversity descriptors including mass-based statistics, elemental"61- [readme] MoleTrans is a webtool for post analysis and data mining on the formula assigned datasets from FT-ICR MS. Alternatively, it can partialy support the combined analysis on the compound annotated results based on other mass spectrometry.: "MoleTrans is a webtool for post analysis and data mining on the formula assigned datasets from FT-ICR MS. Alternatively, it can partialy support the combined analysis on the compound annotated"
HolobiomicsLab