Additional file 1: of Web-TCGA: an online platform for integrated analysis of molecular cancer data sets

The supplemental material includes additional examples and an introduction to the Web-TCGA user interface. (DOCX 1522 kb

Additional file 1: of Serum miR-122-5p and miR-206 expression: non-invasive prognostic biomarkers for renal cell carcinoma

Supplementary Material. (PDF 233 kb

Most relevant representative of GO categories overlapping between PBMC and WB after intervention.

<p>Most relevant representative of GO categories overlapping between PBMC and WB after intervention.</p

Flowchart of data analysis.

<p>Flowchart of data analysis.</p

Variability of methodologies in the processing of gene expression in WB and PBMC.

<p>Variability of methodologies in the processing of gene expression in WB and PBMC.</p

Pathway analysis by overlapping up- and down-regulated genes expressed in PBMC and WB after intervention.

<p>Pathway analysis by overlapping up- and down-regulated genes expressed in PBMC and WB after intervention.</p

Clustered heatmap of the overlapping 333 genes in WB and PBMC shows highly correlated gene expression patterns.

<p>Clustered heatmap of the overlapping 333 genes in WB and PBMC shows highly correlated gene expression patterns.</p

Most relevant representatives of the overlapping up- and down-regulated genes expressed in PBMC and WB between patients after intervention.

<p>Most relevant representatives of the overlapping up- and down-regulated genes expressed in PBMC and WB between patients after intervention.</p

Differentially expressed, highest connected genes sorted by connectivity (n).

<p>Differentially expressed, highest connected genes sorted by connectivity (n).</p

Characteristics of the patients.

<p>Calculations are based on all subjects participating in the study. There were 31 WB samples and 30 PBMC samples from patients and 7 and 3 PBMC and whole blood controls respectively.</p><p>Characteristics of the patients.</p