Modeling of Imaging Mass Spectrometry Data and Testing by Permutation for Biomarkers Discovery in Tissues

Abstract

Exploration of tissue sections by imaging mass spectrometry reveals abundance of different biomolecular ions in different sample spots, allowing finding region specific features. In this paper we present computational and statistical methods for investigation of protein biomarkers i.e. biological features related to presence of different pathological states. Proposed complete processing pipeline includes data pre-processing, detection and quantification of peaks by using Gaussian mixture modeling and identification of specific features for different tissue regions by performing permutation tests. Application of created methodology provides detection of proteins/peptides with concentration levels specific for tumor area, normal epithelium, muscle or saliva gland regions with high confidence.

Mass Spectrometry Imaging: A Review of Emerging Advancements and Future Insights

“…The choice of appropriate univariate analysis tests that one m / z , identifying to a compound of interest, will depend on the data set. If the data has a Gaussian distribution, a t test can be used to determine the difference between two samples with ANOVA being used to determine if there is any difference in a group of samples. , For MSI data sets, t tests can be performed to compare m / z relative intensities between two different regions and ANOVA between three or more regions of interest. For example, peptides and metabolites were evaluated in the cortex region of the brain comparing wild type mice and transgenic mice carrying a missense mutation causing cortical spreading disease, which causes migraines.…”

“…Initially this technique was used to localize proteins and other peptides within a sample, with the first applications toward tissue samples . At first, MALDI was the core technique for imaging, and it is still by far the most popular method for analyzing peptide and protein rich samples. ,, As an example, neuropeptides have been primarily imaged with MALDI, which has been applied to characterizing distribution changes in the pericardial organ of the green crab (red and green morph) after being exposed to salinity stress .…”

Emerging Computational Methods in Mass Spectrometry Imaging

“…Statistical tests assess the likelihood that MS peak intensities are different between sample cohorts. Although t ‐test and analysis of variance (ANOVA) are the most widely used statistical tests, [ 159 , 160 , 161 , 162 , 163 , 164 ] other nonparametric tests that do not assume that data fits a Gaussian distribution including Mann‐Whiney U, [ 165 , 166 , 167 , 168 ] Wilcoxon rank‐sum, [ 169 , 170 ] Kolmogorov–Smirnov, [ 171 ] and Kruskal–Wallis [ 172 ] have also been used for MSI data interpretation. Based on the statistical test results, volcano plots are used to visualize ions with a statistically significant intensity difference between two groups, in which p ‐value and fold‐change value are calculated for each ion.…”

Massive MIMO Codebook Design Using Gaussian Mixture Model Based Clustering

“…Since finite mixture methods have been more popular in recent times are utilized as a combination of two distinct normal distributions to evaluate measurements of a large dataset containing 1000 crab. In diverse fields including medicine [20], sociology [21], physics [22], and several others application fields, Gaussian finite mixture models having proved effective for modeling complicated data.…”