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Bioinformatics ; 38(13): 3490-3492, 2022 06 27.
Artigo em Inglês | MEDLINE | ID: mdl-35608303

RESUMO

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.


Assuntos
Bibliotecas , Software , Espectroscopia de Infravermelho com Transformada de Fourier/métodos , Biblioteca Gênica , Análise de Componente Principal
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