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MotivationWith continually improved instrumentation, Fourier transform infrared (FTIR) microspectroscopy can now be used to capture thousands of high-resolution spectra for chemical characterisation 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.ResultsTo overcome these limitations, we have developed Photizo - an open-source Python library enabling high-throughput spectral data pre-processing, visualisation 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 (FPA) detector.AvailabilityThe 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.

Original publication

DOI

10.1093/bioinformatics/btac346

Type

Journal article

Journal

Bioinformatics (Oxford, England)

Publication Date

24/05/2022

Addresses

Wellcome Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, United Kingdom.