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How to get your goat: automated identification of species from MALDI-ToF spectra
MOTIVATION: Classification of archaeological animal samples is commonly achieved via manual examination of matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) spectra. This is a time-consuming process which requires significant training and which does not produce a measure of conf...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320604/ https://www.ncbi.nlm.nih.gov/pubmed/32176274 http://dx.doi.org/10.1093/bioinformatics/btaa181 |
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author | Hickinbotham, Simon Fiddyment, Sarah Stinson, Timothy L Collins, Matthew J |
author_facet | Hickinbotham, Simon Fiddyment, Sarah Stinson, Timothy L Collins, Matthew J |
author_sort | Hickinbotham, Simon |
collection | PubMed |
description | MOTIVATION: Classification of archaeological animal samples is commonly achieved via manual examination of matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) spectra. This is a time-consuming process which requires significant training and which does not produce a measure of confidence in the classification. We present a new, automated method for arriving at a classification of a MALDI-ToF sample, provided the collagen sequences for each candidate species are available. The approach derives a set of peptide masses from the sequence data for comparison with the sample data, which is carried out by cross-correlation. A novel way of combining evidence from multiple marker peptides is used to interpret the raw alignments and arrive at a classification with an associated confidence measure. RESULTS: To illustrate the efficacy of the approach, we tested the new method with a previously published classification of parchment folia from a copy of the Gospel of Luke, produced around 1120 C.E. by scribes at St Augustine’s Abbey in Canterbury, UK. In total, 80 of the 81 samples were given identical classifications by both methods. In addition, the new method gives a quantifiable level of confidence in each classification. AVAILABILITY AND IMPLEMENTATION: The software can be found at https://github.com/bioarch-sjh/bacollite, and can be installed in R using devtools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-7320604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-73206042020-07-01 How to get your goat: automated identification of species from MALDI-ToF spectra Hickinbotham, Simon Fiddyment, Sarah Stinson, Timothy L Collins, Matthew J Bioinformatics Original Papers MOTIVATION: Classification of archaeological animal samples is commonly achieved via manual examination of matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) spectra. This is a time-consuming process which requires significant training and which does not produce a measure of confidence in the classification. We present a new, automated method for arriving at a classification of a MALDI-ToF sample, provided the collagen sequences for each candidate species are available. The approach derives a set of peptide masses from the sequence data for comparison with the sample data, which is carried out by cross-correlation. A novel way of combining evidence from multiple marker peptides is used to interpret the raw alignments and arrive at a classification with an associated confidence measure. RESULTS: To illustrate the efficacy of the approach, we tested the new method with a previously published classification of parchment folia from a copy of the Gospel of Luke, produced around 1120 C.E. by scribes at St Augustine’s Abbey in Canterbury, UK. In total, 80 of the 81 samples were given identical classifications by both methods. In addition, the new method gives a quantifiable level of confidence in each classification. AVAILABILITY AND IMPLEMENTATION: The software can be found at https://github.com/bioarch-sjh/bacollite, and can be installed in R using devtools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-06-15 2020-03-16 /pmc/articles/PMC7320604/ /pubmed/32176274 http://dx.doi.org/10.1093/bioinformatics/btaa181 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Hickinbotham, Simon Fiddyment, Sarah Stinson, Timothy L Collins, Matthew J How to get your goat: automated identification of species from MALDI-ToF spectra |
title | How to get your goat: automated identification of species from MALDI-ToF spectra |
title_full | How to get your goat: automated identification of species from MALDI-ToF spectra |
title_fullStr | How to get your goat: automated identification of species from MALDI-ToF spectra |
title_full_unstemmed | How to get your goat: automated identification of species from MALDI-ToF spectra |
title_short | How to get your goat: automated identification of species from MALDI-ToF spectra |
title_sort | how to get your goat: automated identification of species from maldi-tof spectra |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320604/ https://www.ncbi.nlm.nih.gov/pubmed/32176274 http://dx.doi.org/10.1093/bioinformatics/btaa181 |
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