Endocrine Related CancerBioinformaticsPeer-reviewed journal article
PPGLomics: An Interactive Platform for Pheochromocytoma and Paraganglioma Transcriptomics
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Abstract
Pheochromocytoma and paraganglioma (PPGL) are rare neuroendocrine tumors with unique biological behavior and remarkably high heritability, yet dedicated bioinformatics resources for these diagnoses remain limited. Existing cancer multi-omics platforms are pan-cancer in scope, often lacking the disease-specific annotations, granularity, and cross-database harmonization required for meaningful stratification and hypothesis generation. Here we introduce PPGLomics, an interactive web-based platform designed for comprehensive PPGL transcriptomics analysis. PPGLomics v1.0 integrates two major datasets, the TCGA-PCPG cohort (n=160) spanning multiple molecular subtypes, and the A5 consortium SDHB cohort (n=91) with detailed clinicopathological and molecular annotations. The platform provides basic and clinical scientists, as well as a broad range of healthcare professionals, with tools for differential expression analysis, correlation analysis, survival analysis, and visualization, including boxplots, heatmaps, volcano plots, and Kaplan-Meier survival plots, enabling exploration of gene expression patterns across PPGL subtypes without requiring bioinformatics expertise. PPGLomics v1.0 is freely available at https://alkaissilab.shinyapps.io/PPGLomics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=51 SRC="FIGDIR/small/702561v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@3b98daorg.highwire.dtl.DTLVardef@b050f4org.highwire.dtl.DTLVardef@1930219org.highwire.dtl.DTLVardef@6edf18_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: clustering
- research focus: dimensionality reduction
- research focus: benchmarking
- approach: statistical model
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