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GEPIA generates dot plots profiling gene/isoform expression across multiple cancer types, paired peritumor, and corresponding GTEx normal samples. Each dot representing a distinct sample.

Parameters:

  • Gene: Input a gene/isoform of interest.
  • |log2FC| Cutoff: Set custom fold-change threshold.
  • q-value: Set custom fold-change threshold.
  • Matched Peritumor / Normal tissue: Select "TCGA paired peritumor + GTEx normal" or "TCGA paired peritumor" for matched normal data in plotting.
  • Dataset Order: Select cancer types of interest in the "TCGA Tumor" field and click "+" to build a dataset list in the "Selected Datasets" field. Manual input of cancer types split by comma (e.g. ACC,BRCA,BLCA) is also acceptable. The x-axis of the plot will follow the order of datasets.
  • Differential Methods: Statistical methods used for differential gene expression analysis.
    DESeq2 uses counts as input, while limma uses log2(TPM + 1)-transformed values as input.

limma
DESeq2

Note: We utilize log2(TPM + 1) for limma and expected counts for DESeq2. For both, we use log scale for visualization.

Tips: Ctrl/Command + A: select all cancer types

GEPIA generates boxplots for comparing expression in several cancer types.

Parameters:

  • Gene: Input a gene/isoform of interest.
  • |log2FC| Cutoff: Set custom fold-change threshold.
  • q-value: Set custom fold-change threshold.
  • Color: Color for significant cohorts
  • Dataset/Tissue Order: Select cancer types of interest in the "TCGA Tumor" field and click "+" to build a dataset list in the "Selected Datasets" field. Manual input of cancer types split by comma (e.g. ACC,BRCA,BLCA) is also acceptable. The x-axis of the plot will follow the order of datasets.
  • Matched Peritumor / Normal tissue: Select "TCGA paired peritumor + GTEx normal" or "TCGA peritumor" as normal data in plotting.
  • Differential Methods:
    The differential analysis here is based on the selected datasets ("TCGA tumor vs TCGA peritumor + GTEx normal" or "TCGA tumor vs TCGA peritumor"). The method for differential analysis is t-test, using disease state (Tumor or Peritumor/Normal) as variable for linear model:

Tips: Ctrl/Command + A: select all cancer types

In this pane, you can profile boxplot to analyze gene expression across various cancer types and stages.

Parameters:

  • Gene: Input a gene/isoform of interest.
  • Plot Color: Set custom fold-change threshold.
  • Dataset/Tissue Order: Select cancer types of interest in the "TCGA Tumor" field and click "+" to build a dataset list in the "Tissue Order" field. Manual input of cancer types split by comma (e.g. ACC,BRCA,BLCA) is also acceptable. The x-axis of the plot will follow the order of datasets.
  • Use Stage: ACJJ tumor stage classification

Tips: Ctrl/Command + A: select all cancer types

This pane generates heatmaps from a gene list. Color density in each block shows the median gene expression in a cohort. It allows comparison of different genes in same tumors or peritumor/normal tissues in one plot.

Parameters:

  • Gene Set: Input genes/isoforms of interest.(num ≥ 2)
  • Log2 (TPM+1) Scale Choose to use log2(TPM+1) transformed expression, while using TPM.
  • Matched Peritumor / Normal tissue: Select "Only TCGA tumor" or "TCGA peritumor + GTEx normal", "TCGA peritumor" for matched normal data in plotting.
  • Dataset/Tissue Order: Select cancer types of interest in the "Dataset" field and click "+" to build a dataset list in the "Tissue Order" field. Manual input of cancer types split by comma (e.g. ACC,BRCA,BLCA) is also acceptable. The x-axis of the plot will follow the order of datasets.

Note: always use log-scale axis for visualization, regardless of whether calculated on log-scale.

Tips: Ctrl/Command + A: select all cancer types

TCGA Abbr.
Abbr Detail
ACC Adrenocortical carcinoma
BLCA Bladder Urothelial Carcinoma
BRCA Breast invasive carcinoma
CESC Cervical squamous cell carcinoma and endocervical adenocarcinoma
CHOL Cholangiocarcinoma
COAD Colon adenocarcinoma
DLBC Lymphoid Neoplasm Diffuse Large B-cell Lymphoma
ESCA Esophageal carcinoma
GBM Glioblastoma multiforme
HNSC Head and Neck squamous cell carcinoma
KICH Kidney Chromophobe
KIRC Kidney renal clear cell carcinoma
KIRP Kidney renal papillary cell carcinoma
LAML Acute Myeloid Leukemia
LGG Brain Lower Grade Glioma
LIHC Liver hepatocellular carcinoma
LUAD Lung adenocarcinoma
LUSC Lung squamous cell carcinoma
MESO Mesothelioma
OV Ovarian serous cystadenocarcinoma
PAAD Pancreatic adenocarcinoma
PCPG Pheochromocytoma and Paraganglioma
PRAD Prostate adenocarcinoma
READ Rectum adenocarcinoma
SARC Sarcoma
SKCM Skin Cutaneous Melanoma
STAD Stomach adenocarcinoma
TGCT Testicular Germ Cell Tumors
THCA Thyroid carcinoma
THYM Thymoma
UCEC Uterine Corpus Endometrial Carcinoma
UCS Uterine Carcinosarcoma
UVM Uveal Melanoma

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