Top used analysesΒΆ

A univariable survival analysis between a molecular variable and patient overall survival (OS), progression-free survival (PFS), disease-free survival (DFS), etc.
A differential analysis using a rank-sum test (Wilcoxon or Kruskal-Wallis, default) or student t-test in 2 or more than 2 groups.
Pearson or spearman (default) correlation analysis between two variables.
Mutation count bar plot. Can be grouped by any clinical feature, such as ER, PR, Her2 status, if available.
Driver mutation enrichment analysis. This analysis calculates whether a gene mutation is enriched in two different patient cohorts (e.g., ER+ vs. ER-). A chi-square test is performed.
Mutation signature summary heatmap. Hierarchical clustering is performed by default.
A caterpillar plot can be used to visualize mutation count, number of neoantigens, and any other numeric variables.
Mutation lollipop. If a mutation occurred in a coding gene, UniProt canonical protein sequence and Pfam domain annotation are annotated as the x-axis. If a mutation occurred in a non-coding region, the chromosome position is used to show the mutation position.
A boxplot with scatter dots can be applied to visualize the number of samples, mutation counts, number of neoantigens, or any other numeric variables.
A stacked bar plot can be used to visualize mutation signatures and any numeric variables.
A pie chart is used to summarize categorical variables in a sample cohort, such as gender, stage, grade, tissue, race, etc.
A histogram plot is used to summarize numeric variables in a sample cohort, such as age, survival time, time of initial diagnosis, etc.
A waterfall plot (mutation landscape) visualizes the mutation and copy number variation in a sample cohort.