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. 2022 Nov 22;13:7171. doi: 10.1038/s41467-022-34917-y

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© The Author(s) 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 5 — a, b Volcano plots representation of differential gene expression pattern induced by doxorubicin-only (a) or dexamethasone/doxorubicin combination treatment (b) over vehicle-treated control in nine rs28714259 intrinsically polymorphic hiPSC-derived cardiomyocyte cell (hiPSC-CM) lines. Tests for differential expression were performed with DESeq2 package in R using a negative binomial generalized linear model (two-sided test). The p-values were then corrected for multiple hypothesis testing using the False Discovery rate (FDR) approach of Benjamini–Hochberg. An FDR < 0.05 were considered statistically significant. Significantly differentially expressed genes (FDR < 0.05) of Log2 Fold Change (|log2FC|) > 1 are highlighted in red, while those of |log2FC| < 1 are highlighted in blue. Black and orange highlights represent genes with FDR > 0.05. Top differentially expressed genes are labeled. c Heat map of gene expression patterns in vehicle control, dexamethasone-only, doxorubicin-only, and dexamethasone/doxorubicin combination treatment groups. Top 50 genes most differentially regulated by doxorubicin treatment (|Log2FC > 1|, ranked by P-value) are shown. d Heat map of top 50 most differentially regulated genes between doxorubicin-only and dexamethasone/doxorubicin combination treatments based on ΔLog2FC in nine rs28714259 intrinsically polymorphic hiPSC-CM lines. e Heat map of differential gene expression induced by dexamethasone/doxorubicin combination treatment significantly impacted by the risk (A) allele. Differential gene expression after treatment for each sample was normalized to its baseline (control) expression (d, e). f Top pathways differentially regulated by the risk (A) allele following doxorubicin or dexamethasone and doxorubicin combination treatment identified by IPA. Benjamini-Hochberg (B-H) adjusted p-values were calculated in IPA to account for multiple comparisons, and the B-H adjusted p-value < 0.05 was considered as statistically significant. Percentage of pie chart is proportional to the number of genes identified in each pathway. Pathways are ordered clockwise by P-value. TX treatment, GT genotype, DOX doxorubicin, DD dexamethasone/doxorubicin combination. Source data for Fig. 5a–f are provided as a Source Data file.