cibersort deconvolution Search Results


cibersort deconvolution  (Proteostasis Therapeutics)
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Proteostasis Therapeutics cibersort deconvolution
Immune infiltration analysis. (A) Relative proportions of immune cell subpopulations in the control and sepsis groups. (B) Correlation matrix illustrating the associations between different immune cell types. Red indicates a positive correlation, and blue indicates a negative correlation; the intensity of the color and the size of the circles correspond to the strength of the correlation coefficient. (C) Comparison of immune cell abundance between the control and sepsis groups. Blue represents the control group, while yellow represents the sepsis group. (Note: These results are based on <t>CIBERSORT</t> <t>deconvolution</t> of bulk transcriptomic data). (D–G) Correlation analysis between the identified candidate genes and the infiltration levels of various immune cell types. *: p<0.05, **: P<0.01, ***: P<0.001, ns: not significant.
Cibersort Deconvolution, supplied by Proteostasis Therapeutics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/cibersort+deconvolution/cibersort+deconvolution/pmc13253298-215-6-17
Average 86 stars, based on 1 article reviews
cibersort deconvolution - by Bioz Stars, 2026-09
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Immune infiltration analysis. (A) Relative proportions of immune cell subpopulations in the control and sepsis groups. (B) Correlation matrix illustrating the associations between different immune cell types. Red indicates a positive correlation, and blue indicates a negative correlation; the intensity of the color and the size of the circles correspond to the strength of the correlation coefficient. (C) Comparison of immune cell abundance between the control and sepsis groups. Blue represents the control group, while yellow represents the sepsis group. (Note: These results are based on CIBERSORT deconvolution of bulk transcriptomic data). (D–G) Correlation analysis between the identified candidate genes and the infiltration levels of various immune cell types. *: p<0.05, **: P<0.01, ***: P<0.001, ns: not significant.

Journal: Frontiers in Cellular and Infection Microbiology

Article Title: A synergistic multi-omics approach: causal sepsis drivers identified in activated CD4 + T cells by single-cell RNA sequencing and Mendelian randomization

doi: 10.3389/fcimb.2026.1749207

Figure Lengend Snippet: Immune infiltration analysis. (A) Relative proportions of immune cell subpopulations in the control and sepsis groups. (B) Correlation matrix illustrating the associations between different immune cell types. Red indicates a positive correlation, and blue indicates a negative correlation; the intensity of the color and the size of the circles correspond to the strength of the correlation coefficient. (C) Comparison of immune cell abundance between the control and sepsis groups. Blue represents the control group, while yellow represents the sepsis group. (Note: These results are based on CIBERSORT deconvolution of bulk transcriptomic data). (D–G) Correlation analysis between the identified candidate genes and the infiltration levels of various immune cell types. *: p<0.05, **: P<0.01, ***: P<0.001, ns: not significant.

Article Snippet: While we partially addressed this via CIBERSORT deconvolution to explore neutrophil-related correlations, their specific contribution to the ‘Metabolism–Proteostasis–Immunity’ axis may not be fully captured at the single-cell level.

Techniques: Control, Comparison