CoD
Computational Tool
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DescriptionInferring immune-cell quantities related to disease states
Homepagehttp://www.csgi.tau.ac.il/CoD/
Publications
CoD: inferring immune-cell quantities related to disease states
Amit Frishberg; Yael Steuerman; Irit Gat-Viks
Motivation: The immune system comprises a complex network of genes, cells and tissues, coordinated through signaling pathways and cell−cell communications. However, the orchestrated role of the multiple immunological components in disease is still poorly understood. Classifications based on gene-expression data have revealed immune-related signaling pathways in various diseases, but how such pathways describe the immune cellular physiology remains largely unknown.
Results: We identify alterations in cell quantities discriminating between disease states using ‘ Cell type of Disease’ (CoD), a classification-based approach that relies on computational immune-cell decomposition in gene-expression datasets. CoD attains significantly higher accuracy than alternative state-of-the-art methods. Our approach is shown to recapitulate and extend previous knowledge acquired with experimental cell-quantification technologies.
Conclusions: The results suggest that CoD can reveal disease-relevant cell types in an unbiased manner, potentially heralding improved diagnostics and treatment.
Availability and implementation: The software described in this article is available at http://www.csgi.tau.ac.il/CoD/.
Contact: iritgv@post.tau.ac.il
Supplementary information: Supplementary data are available at Bioinformatics online.
DOI: https://doi.org/10.1093/bioinformatics/btv498
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