Reference: Kaur H et. al., (2019) Classification of early and late stage liver hepatocellular carcinoma
patients from their genomics and epigenomics profiles. PLoS One. 14(9):e0221476.


Predicting Cancer Status of a Batch of subjects from RNA expression and Methylation status of Signature RNA and CpG sites Data

This tool predict the status of patient or subject based on 51 signature features (30RNA transcripts and 21 CpG sites) resulting from analysis of RNA expression (RNA seq data) and CpG site associated methylation array data of Liver Hepatocellular Carcinoma from TCGA dataset from GDC Data portal. Here, the users requires to submit FPKM values of 30 signature RNA transcripts and methylation beta values of 21 signature CpG sites (Probe IDs associated with CpG sites) to predict the cancer status of subjects. This method predict cancer status whether subject is in Stage-I or late stage of LIHC. The first column is RNA transcript or CpG sites and in second column FPKM value or methylatin level of corresponding RNA trancsript or CpG site in a particular number of patients. For more information please click Help.

Submit csv file in which each number represents the Methylation beta value derived CpG sites methylation array intensity data of the Liver Hepatocellular Carcinoma:



   Example csv file    Choose SVM threshold:                   SVM threshold is required for prediction. Moving the threshold value in either direction (positive or negative) will lead to increase in probability of correct prediction in that direction