Fig. 1 | Scientific Reports

Fig. 1

From: A bioinformatics-driven approach to identify biomarkers and elucidate the pathogenesis of type 2 diabetes concurrent with pulmonary tuberculosis

Fig. 1

Clarification of the relationship between C1q expression levels and PTB + T2DM. (A–F) We retrieved the RNA-seq chip data from the GSE181143 dataset, which integrates diabetes with pulmonary tuberculosis, from the GEO database utilizing the R package GEOquery. Subsequently, we conducted a comprehensive analysis of differential expression employing the R package limma. Lastly, we produced a visually informative volcano plot to elucidate the distinctive patterns of gene expression alterations within the dataset. Volcano plots of DEGs of the following group comparisons: T2DM (n = 70) vs. PTB (n = 207) (A); T2DM (n = 70) vs. HC (n = 90) (B); PTB + T2DM (n = 193) vs. HC (n = 90) (C); PTB + T2DM (n = 193) vs. T2DM (n = 70) (D); PTB (n = 207) vs. HC (n = 90) (E); and PTB + T2DM (n = 193) vs. PTB (n = 207) (F). The red spots represent upregulated genes with a log2 (fold change) of > 1 (right vertical dashed line) and false discovery rate < 0.05 (horizontal dashed line), and the green spots represent the downregulated genes with a log2 (fold change) of < −1 (left vertical dashed line) and false discovery rate < 0.05.

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