Fig. 3: Decomposition benchmark in human subcutaneous adipose tissue. | Nature Communications

Fig. 3: Decomposition benchmark in human subcutaneous adipose tissue.

From: Accurate estimation of cell composition in bulk expression through robust integration of single-cell information

Fig. 3

a Comparison of decomposition estimates from 100 individuals with estimates from 6 individuals with snRNA-seq data available. Each color represents a benchmarked method. Boxes indicate the quartiles of the estimated proportions with whiskers extending 1.5 times the interquartile range. Points are individual samples that are represented by the boxplot. b, c Scatterplots comparing decomposition estimates with measured phenotypes in 100 individuals. Reported ‘rho’ corresponds to Spearman correlation and p-values indicate the significance of these correlations, with an asterisk denoting significance after correction for covariates in a linear-mixed model. CIBERSORT and BSEQ-sc are not shown as they did not detect these cell populations. These examples include the most abundant (adipocytes) and rarest (T cells) cell types identified in the snRNA-seq data. Significance of associations reported in Supplementary Table 1. b Adipocyte proportion has been observed to negatively correlate with BMI so we expected a negative correlation. Bisque (p = 0.030) and CIBERSORTx (p = 0.001) produced significant negative associations after correcting for sex, age, age-squared, and relatedness in a linear-mixed model. c T-cell proportion has previously been reported to positively correlate with insulin resistance. Matsuda index decreases with higher insulin resistance so we expected a negative correlation. Bisque (p = 0.002) and CIBERSORTx (p = 0.046) produced significant negative associations after correcting for diabetes status, sex, age, age-squared, and relatedness in a linear-mixed model. Source data are provided as a Source Data file.

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