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This mutation portal provides an interactive interface to predictions by CHASMplus. CHASMplus is a machine learning algorithm that discriminates somatic missense mutations as cancer drivers. We summarize results with interactive widgets, provide search capability and an interactive table of results. Visualizations include:

  • Mutations on protein structure
  • Lollipop diagrams
  • Number of driver mutations per gene
  • Breakdown of mutation frequency
  • Distribution of CHASMplus scores

Search by gene

Enter in the HUGO gene symbol at the top of the page to search for all predicted driver mutations for a particular gene.

Figure 1

Summary plots

All searches will dynamically change the summary plots.

Table

The table provides a listing of all predicted driver mutations meeting your search criteria.

Figure 2

Analysis type:

We performed analysis with CHASMplus in two different manners. The first called “pan-cancer” aggregates mutations from multiple cancer types together, while the second was done by analyzing each cancer type separately (“cancer type-specific”). You can select which analysis you want to examine by using the dropdown menu (see Marker #1).

In the case of the pan-cancer results where multiple cancer types contain the same mutation, the listed cancer type has the highest mutation frequency.

Toggle columns:

You can toggle the display of columns by checking/unchecking boxes (see Marker #2).

Search capabilities:

You may enter multiple combinations of searches by using the advanced searches available on the table.

  • Filter by gene name (exact match, see Marker #3)
  • Filter by mutation (fuzzy match, see Marker #4)
  • Filter by mutations with at least a certain CHASMplus score (see Marker #5)
  • Filter by cancer type (see Marker #6)
  • Filter by the mutation frequency of the driver mutation (common, intermediate, or rare, see Marker #7)

Additional variant information:

By clicking on the “More details” link for each variant (see Marker #8), CRAVAT provides more information on the variant, including a lollipop plot, protein structure viewer and gene network graph. You can read help about using these widgets from the CRAVAT and MuPIT help pages.

Figure 3

Download data:

You can download data in either excel format (.xlsx file) or as a csv file (see Marker #9). You can also download the complete list of TCGA patient IDs used in this analysis here.