Photizo: an open-source library for cross-sample analysis of FTIR spectroscopy data

Author:

Grant-Peters Melissa1,Rich-Griffin Charlotte1,Grant-Peters Jonathan E2,Cinque Gianfelice3,Dendrou Calliope A1ORCID

Affiliation:

1. Nuffield Department of Medicine, Wellcome Centre for Human Genetics, University of Oxford , Oxford OX3 7BN, UK

2. Mathematical Institute, University of Oxford , Oxford OX2 6GG, UK

3. Diamond Light Source , Didcot OX11 0DE, UK

Abstract

Abstract Motivation With continually improved instrumentation, Fourier transform infrared (FTIR) microspectroscopy can now be used to capture thousands of high-resolution spectra for chemical characterization of a sample. The spatially resolved nature of this method lends itself well to histological profiling of complex biological specimens. However, current software can make joint analysis of multiple samples challenging and, for large datasets, computationally infeasible. Results To overcome these limitations, we have developed Photizo—an open-source Python library enabling high-throughput spectral data pre-processing, visualization and downstream analysis, including principal component analysis, clustering, macromolecular quantification and mapping. Photizo can be used for analysis of data without a spatial component, as well as spatially resolved data, obtained e.g. by scanning mode IR microspectroscopy and IR imaging by focal plane array detector. Availability and implementation The code underlying this article is available at https://github.com/DendrouLab/Photizo with access to example data available at https://zenodo.org/record/6417982#.Yk2O9TfMI6A.

Funder

Wellcome Trust and Royal Society

BBSRC

Multiple Sclerosis Society Tissue Bank

Multiple Sclerosis Society of Great Britain and Northern Ireland

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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