Computational Tools and Analysis Section
Overview
This section provides an indexed list of computational methods, software packages, scripts, and analytical tools utilised within bioarchaeological research as described in the Manual. Each listed tool includes a concise description, intended application, and links to relevant webpages and GitHub repositories, including specific guidance on usage, robustness, error analysis, and reliability criteria.
Tools by Application
Proteomics
MaxQuant
Description: Comprehensive quantitative proteomics software suite designed for analysing large mass-spectrometry data.
Webpage: MaxQuant
Repository: GitHub/MqTools7
License: Freeware (proprietary but freely available)
Reliability Criteria: Robust peptide identification with built-in false discovery rate (FDR) assessment.
MetaMorpheus
Description: Software for high-throughput proteomics with enhanced sensitivity and comprehensive search capabilities.
Webpage: MetaMorpheus
Repository: GitHub/MetaMorpheus
License: Open-source (MIT License)
- Documentation:
Spectronaut
License: Proprietary (commercial license)
Website: biognosys.com/software/spectronaut
Scaffold
License: Proprietary (per device license)
Website: proteomesoftware.com
Comet
License: Open-source (Apache License 2.0)
Website: https://uwpr.github.io/Comet/
SPIN (Species by Proteome INvestigation) workflow
Lipid Analysis
MassHunter
Description: Software for acquiring and processing mass spectrometry data, tailored especially for gas chromatography (GC-MS, GC-FID).
Webpage: MassHunter Software
Reliability Criteria: Internal QC via blank subtraction and retention-time alignment.
Omnic
Description: Software suite for Fourier-transform infrared (FTIR) spectroscopy that can be used for lipid analysis and interpretation.
Webpage: ThermoFisher Scientific - Omnic
Reliability Criteria: Offers extensive data validation tools for robust spectral analysis.
Microfossil Analysis
C
Radiocarbon Dating
OxCal
Description: Calibration software for radiocarbon dating, widely used for converting radiocarbon years (BP) to calendar dates.
Webpage: OxCal Calibration Software
Instructions: Detailed workflows available in OxCal Online Manual
Reliability Criteria: Includes statistical tools to manage calibration uncertainties and evaluate date reliability.
rcarbon (R package)
Description: An R package for calibration and statistical analysis of radiocarbon dates.
Repository: GitHub/rcarbon
Instructions: Package documentation available online; supports reproducible data analysis workflows.
Stable Isotope Analysis
IsoReader
Description: Software for standardized reading, processing, and managing stable isotope data.
Repository: GitHub/IsoReader
Instructions: Extensive documentation and examples provided in the repository.
MixSIAR
Description: Bayesian mixing model designed to analyze stable isotope data, useful for diet reconstruction studies.
Repository: GitHub/MixSIAR
Reliability Criteria: Model robustness checked via diagnostic statistics and sensitivity analysis.
ZooMS Analysis
mMass
Description: Open-source mass spectrometry software for ZooMS data analysis.
Webpage: mMass
Repository: GitHub/mMass
Instructions: Protocols.io guide available here.
Reliability Criteria: Software supports detailed spectral analysis and robust species identification through peptide markers.
General Guidelines for Computational Tools
GitHub Repositories:
Scripts used in data processing and analysis are archived and publicly accessible via GitHub. Repository details include commit histories and version control for reproducibility.
Instructions for Usage:
Each computational tool comes with clearly documented instructions. Usage protocols include required data formats, step-by-step execution guidance, and troubleshooting sections.
Robustness and Error Analysis:
Analytical scripts and software provide error handling and robustness checks, including internal quality controls, validation datasets, and repeat analyses for accuracy verification.
Reliability Criteria:
Tools have been selected based on peer-reviewed reliability, robustness of results, reproducibility, and community endorsement within bioarchaeological research contexts.
This structured documentation supports the consistent use and rigorous application of computational methodologies within bioarchaeological investigations, fostering transparent and reproducible research practices.