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The RNA-seq web tool contains complex functions for mining cancer-related lncRNAs including general information, differential expression analysis, box plotting, stage plotting, survival analysis, similar lncRNAs identification, correlation analysis, network construction and TF motif prediction. The datasets in current RNA-seq web tools are obtained from TCGA containing 15878 lncRNAs, 33 cancer types, 9664 tumor and 711 normal control samples. View our Help page for cancer abbreviations and further help.
This function provides general information including subcellular localization, functions, Gene ontology annotation, mean expression in cancer and normal tissue and box plots in all kinds of cancers for a specific lncRNA.
This function allows user to obtain differential expression analysis and heatmap for lncRNAs in a specific cancer. This feature allows user to apply custom statistical methods and thresholds on a given kind of cancer.
This function generates box plots for comparing expression of a specific lncRNA between cancer and normal samples. This feature allows user to apply custom color for box plots of cancer and normal group.
The functions generates expression violin plot for a specific lncRNA based on patient pathological stage. This feature allows user to select major and detailed cancer stages.
This function performs overall survival (OS) or disease free survival (DFS, also called relapse-free survival and RFS) analysis based on a specific lncRNA expression. This feature allows user to apply custom OS, DFS, median and quantile expression value of a lncRNA.
This function identifies a list of lncRNAs with similar expression pattern for an input lncRNA and selected datasets.
This function provides lncRNA expression correlation analysis for two interested lncRNAs in a cancer. This feature allows user to apply custom correlation analysis methods including Pearson, Spearman and Kendall.
This function provides interacted miRNA-lncRNA and mRNA-lncRNA co-expressed networks.
This function predicts TF motif for a specific lncRNA and provides TF motif sequence LOGO figure.
General
This function provides general information including subcellular localization, functions, Gene ontology annotation, mean expression in cancer and normal tissue and box plots in all kinds of cancers for a specific lncRNA.
LncRNA
Differential Expression Analysis (DEA)
This function allows user to obtain differential expression analysis and heatmap for lncRNAs in a specific cancer. This feature allows user to apply custom statistical methods and thresholds on a given kind of cancer.
CancerName: Select a cancer for differential analysis.
Method: Select a method for differential analysis.
log2FC: Select a threshold value of fold change for differential analysis.
FDR: Select a threshold value of fdr for differential analysis.
Expression on Box Plots
This function generates box plots for comparing expression of a specific lncRNA between cancer and normal samples.
This feature allows user to apply custom color for box plots of cancer and normal group.
Kruskal-Wallis test was used to analyze the difference of the gene expression level between cancer and normal samples.
LncRNA: Select a lncRNA for drawing the boxplot.
CancerName: Select a cancer for drawing the boxplot.
Color Select: Select a color for drawing the boxplot.
Stage Plot
The function generates expression violin plot for a specific lncRNA based on patient pathological stage. This feature allows user to select major and detailed cancer stages.
Kruskal-Wallis test was used to analyze the difference of the gene expression level in the stages of cancer.
LncRNA: Select a lncRNA for drawing the violin plot of cancer stages.
CancerName: Select a cancer for drawing the violin plot of cancer stages.
Color Select: Select a color for drawing the violin plot of cancer stages.
Major Stage: Select major pathological stage or detailed pathological stage for drawing the violin plot of cancer stages.
LncRNA Survival
This function performs overall survival (OS) or disease free survival (DFS, also called relapse-free survival and RFS) analysis based on a specific lncRNA expression. This feature allows user to apply custom OS, DFS, median and quantile expression value of a lncRNA. Kaplan-Meier survival analysis is performed for the two clustered groups and statistical significance assessed using the log-rank test.
LncRNA: Select a lncRNA for drawing the Survival curve.
Group Cutoff: Select a threshold value for drawing the Survival curve.
Methods: Select a method for drawing the Survival curve.
Dataset Select: Select a Cancer for drawing the Survival curve.
Similar LncRNA
This function identifies a list of lncRNAs with similar expression pattern for an input lncRNA and selected datasets. The constraint condition of the identified lncRNAs and the input lncRNA is that the correlation coefficient is greater than 0.8 and p < 0.05.
LncRNA: Select a lncRNA for defining similar lncRNAs.
Dataset Select: Select a cancer for defining similar lncRNAs.
Correlation Coefficient: Select a method for defining similar lncRNAs.
LncRNA Correlation Analysis
This function provides lncRNA expression correlation analysis for two interested lncRNAs in a cancer. This feature allows user to apply custom correlation analysis methods including Pearson, Spearman and Kendall.
LncRNA A: Select a lncRNA A for drawing the scatter diagram.
LncRNA B: Select a lncRNA B for drawing the scatter diagram.
Dataset Select: Select a cancer for drawing the scatter diagram.
Point Color: Select a color for drawing the scatter diagram.
Correlation Coefficient: Select a method for drawing the scatter diagram.
Co-expression Network
This function provides interacted miRNA-lncRNA and mRNA-lncRNA co-expressed networks based on pearson correlation analysis.
LncRNA: Select a lncRNA for drawing the network.
Dataset Select: Select a cancer for drawing the network.
p value: Select a p value for drawing the network.
RNA type: Select a RNA type for drawing the network.
TF motif
This function predicts TF motif for a specific lncRNA and provides TF motif sequence LOGO figure. TF and lncRNA interactions are predicted by MEME Suite. The TF motif sequence LOGO figures are performed by ggseqlogo package with the default parameters.
lncRNA: Select a lncRNA to acquire TF motif.
q value: Select a q value to acquire TF motif.