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An integrated approach for analyzing spatially resolved multi-omics datasets from the same tissue section
As spatial biology methods mature, users are increasingly combining multiple readouts for a holistic view of tissue biology. This paper presents a software and a computational framework for integration and data analysis of same-section spatial transcriptomics and spatial proteomics data acquired using different spatial platforms.
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Integration of Multiple Spatial Omics Modalities Reveals Unique Insights into Molecular Heterogeneity of Prostate Cancer
In this preprint, we integrated spatial transcriptomics, mass spectrometry-based lipidomics, single nucleus RNA-seq and histomorphological information from human prostate cancer patient samples. This provided novel insights into correlating genes and lipids linked to distinct cell populations and histopathological disease states, as well as comparisons across samples in a tissue cohort.
Cancer Research
Exploratory Analyses
lipidomics
mass spectrometry imaging
spatial transcriptomics
Integrating Ambient Ionization Mass Spectrometry Imaging and Spatial Transcriptomics on the Same Cancer Tissues to Identify RNA–Metabolite Correlations
This study presents a novel workflow for mapping the location and abundance of mRNA and metabolites from the same tissue section, allowing identification of thousands of spatially correlating genes and metabolites.
lipidomics
mass spectrometry imaging
Exploratory Analyses
Cancer Research
spatial technologies
Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture
This paper demonstrates an approach for conducting quantitative mass spectrometry imaging (MSI) of lipids directly from brain tissue sections. This greatly expands the utility of MSI for spatial lipidomics.
lipidomics
mass spectrometry imaging
central nervous system
Exploratory Analyses
Classification of cirrhotic patient samples based on imaging MS of multiplexed N-glycan markers in biofluids.
This poster is an example of how Aspect Analytics can be your partner to develop specialized bioinformatic and data analysis workflows for your specific use-case or application.
Pathway Analyses
Targeted Analyses
Annotation Studio: a web portal to support the development of IMS-based diagnostic assays
In this poster we showcased Annotation Studio, a software solution we co-developed with Frontier Diagnostics to aid them in annotating whole-slide images to develop MALDI imaging-based diagnostic assays.
Other
Diagnosis of melanoma by imaging mass spectrometry: Development and validation of a melanoma prediction model
In this joint work we partnered with Frontier Diagnostics, Vanderbilt and several board certified pathologists to develop a classification model capable of distinguishing melanoma from benign nevus tissue, using a MALDI-imaging based proteomics assay.
Cell segmentation / typing
Spatially-Aware Clustering of Ion Images in Mass Spectrometry Imaging Data Using Deep Learning
In this work, we use a pre-trained neural network to extract high-level features from ion images in MSI data, and test whether this improves downstream data analysis
Spatially-aware Clustering
Metabolite Explorer: A Software Tool for Targeted Analysis of Mass Spectrometry Imaging Data
In this poster we introduce Metabolite Explorer, a software tool that facilitates high-throughput, targeted data analysis, given data from multiple MSI experiments.
Exploratory Analyses
Spatially-Aware Clustering of Ion Images in Mass Spectrometry Imaging Data Through the Use of Pre-trained Neural Networks
This project concerns improving unsupervised methods to cluster ion images, which enables identifying m/z bins with similar spatial expressions.
No items found.
Rapid Bioinformatics Prototyping Based on a Public Application Programming Interface
The goal of this joint poster with Bruker and University of Bremen was to demonstrate a new API for reading data files in SCiLS Lab format. In this joint work, two use-cases were developed based on this API.
UMAP
Unsupervised Machine Learning for Exploratory Data Analysis in Imaging Mass Spectrometry
In this review paper we give an extensive overview of the wide range of unsupervised machine learning methods that have been applied in the analysis of Mass Spectrometry Imaging (MSI) data.
Other
Evaluation of Distance Metrics and Spatial Autocorrelation in Uniform Manifold Approximation and Projection Applied to Mass Spectrometry Imaging Data
In this work, we explored the utility of a recently introduced, nonlinear dimensionality reduction method named Uniform Manifold Approximation (UMAP) for MSI data analysis.
Cell segmentation / typing
UMAP