Data parsing in mass spectrometry imaging using R Studio and Cardinal: A tutorial
| Autor: | Cameron Shedlock, Katherine Stumpo |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
PCA
principal component analysis SNR signal to noise ratio Clinical Biochemistry DESI desorption electrospray ioniziation Data validation AuNP gold nanoparticle IACUC Institutional Animal Care and Use Committee Microbiology MSI mass spectrometry imaging RAM random access memory TIC total ion current Mass spectrometry imaging Medical Laboratory Technology SSD solid state drive RMS root mean squared Medical technology R Studio SSC spatial shrunken centroid R855-855.5 Special issue on Data Science ITO indium tin oxide Cardinal Spectroscopy |
| Zdroj: | Journal of Mass Spectrometry and Advances in the Clinical Lab, Vol 23, Iss, Pp 58-70 (2022) Journal of Mass Spectrometry and Advances in the Clinical Lab |
| ISSN: | 2667-145X |
| DOI: | 10.1016/j.jmsacl.2021.12.007 |
| Popis: | Mass spectrometry imaging (MSI) has emerged as a rapidly expanding field in the MS community. The analysis of large spectral data is further complicated by the added spatial dimension of MSI. A plethora of resources exist for expert users to begin parsing MSI data in R, but there is a critical lack of guidance for absolute beginners. This tutorial is designed to serve as a one-stop guide to start using R with MSI data and describe the possibilities that data science can bring to MSI analysis. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect