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      • Prediction using 8 genes
      • Prediction using 10 genes
      • Prediction using 64 genes
      • Prediction using 38 genes(Cancer Hallmark Genes)
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Reference: Bhalla et. al. (2017) Gene expression-based biomarkers for discriminating early and late stage of clear cell renal cancer. Scientific Reports, 7, 44996

Home Page of cancerCSP

CancerCSP (clear cell renal cancer stage prediction) is a web-bench developed for predicting Early and Late stage of clear cell renal cell carcinoma (ccRCC) patients using gene expression data derived from RNA-seq experiments in the form of RNA-Seq by Expectation Maximization (RSEM) values. The user can also analyze data regarding expression of a gene in early and late stage of ccRCC for any gene among 20,531 genes included in TCGA analysis. The models used in this study were trained on TCGA genomics Level 3 data for cancer patients of 519 cancer patients. We are able to discriminate early and late stage patients with accuracy of 72.64% with ROC of 0.78 on validation dataset.


Major Features


  • Genomics Based Prediction: This module allow users to predict cancer status(Early and Late) of a cancer patient from its genomics expression data. In this case user need to provide RSEM values of particular genes that includes its HGNC gene symbol, and its respective RSEM value.
  • Gene wise analysis: This analysis gives the status of user given genes in the TCGA data. This server also provides the threshold based ROC calculated for each gene to access its capability of classifying the sample into early or late stage. User can check its gene of interest from the genes present in TCGA data, its expression in case of early stage patients and late stage patients. Its p value, calculated using Wilcoxon test, showing whether there is significant difference in the expression of gene in early and late stages of ccRCC.


  • cancerCSP
    Raghava's Group
    IMTECH
    CRDD
    CancerPPD
    Cancertope