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External References: Wikipedia National Cancer Institute Google Scholar

iCoMut Beta for

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Mutation Rate Panel
Somatic mutation rate per patient stratified by synonymous and non synonymous mutations. The mutation rate is calculated as number of mutations per million bases.

Change Y axis maximum:

Clinical Age Panel
Age is classified into low, middle and high groups by 1/3 and 2/3 quantile (Q) of age vector.

low: age <= 1/3 Q.
middle: 1/3 Q < age < 2/3 Q.
high: age >= 2/3 Q.

Vital Status Panel

Gender Panel

Histology Panel

Ethnicity Panel

Gene Mutation Panel

Focal Level Copy Number Gain Panel Somatic focal copy number gain events identified by GISTIC, color-coded by type of alterations (see color legend).
Deletion:
log2(CN ratio) <= -1

Loss:
-1 < log2(CN ration) < -0.42

Gain:
0.58 < log2(CN ration) < 1.3

Amplification:
log2(CN ratio) >= 1.3

Focal Level Copy Number Loss Panel Somatic focal copy number loss events identified by GISTIC, color-coded by type of alterations (see color legend).
Deletion:
log2(CN ratio) <= -1

Loss:
-1 < log2(CN ration) < -0.42

Gain:
0.58 < log2(CN ration) < 1.3

Amplification:
log2(CN ratio) >= 1.3

CN cNMF Cluster Panel

Methylation cNMF

RPPA cNMF Cluster Panel

RPPA cHierarchical Cluster Panel

mRNAseq cNMF Cluster Panel

mRNAseq cHierarchical cNMF Cluster Panel

miRseq cNMF Cluster Panel

miRseq cHierarchical Cluster Panel

miRseq Mature cNMF Cluster Panel

miRseq Mature cHierarhical Cluster Panel:

Samples are sorted by ...

iCoMut Documentation

Current Release: Beta.

Comut plot, introduced by Nicolas Stransky, is often seen in cancer research publications as a visual summary of genetic variations/mutations in cancer cohorts. The plot itself is essentially an ensemble of multiple smaller and simpler plots (e.g. heat maps and bar graphs) aligned and interconnected via a common X or Y axis. This form of grid-like graphical summary is particularly suitable for presenting data with an intricate and associative nature. iCoMut aims to further transform the static image into an interactive data exploring experience that is flexible and versatile, and through a web-enabled user interface, provides greater public access.

Broad TCGA GDAC data and analyses summaries provided by Jaegil Kim, Hailei Zhang, Juok Cho, and David Heiman.
iCoMut is developed by Katherine Huang, Nome Shoresh, Eila Arich-Landkof, Michael Noble, Gad Getz at Broad Institute.

Tutorial

Data Sorting

By default, patients in a cancer cohort are sorted first by the histological subtypes (if available), then by the gene mutations.

Data can be sorted by clicking on the text labels of the axes and the heat maps. To perform a multi-key sorting, alt-click on a text label to add a key.

The info box located on the left reports the sorting status of the patients.

Many options to sort patients can be done by mouse clicking. Here, for example, patients are sorting by age (click) then by focal-level copy number gain (alt-click on "Multi-Key Sort" located above the copy number heat map).

Rearranging Panel Layout

A panel can be collapsed by clicking on the minus icon.

Horizontal panels can be rearranged by drag and drop using the minus/plus icons located on the left of the panel titles.

Collapse and Expand All

Control buttons, for collapsing and expanding all panels, are conveniently provided at the top of the comut plot. Additionally, by first collapsing all panels, the rearrangement of the layout order of panels can be done more easily by drag and dropping the plus sign next the panel title.

Interactive Heat Map

Clicking (or alt-clicking) a row name will sort the columns (i.e. patients) by the row. The sorting order is toggled by clicking the same row name again.
Additionally, users can easily rearrange the order of rows by dragging and dropping the row names.

Clicking 'Show Grids' will show all the rectangles in a heat map, including the ones with no data. When in this mode, the cross-hair cursor is also shown. The cursor can be locked in at a rectangle by double-clicking. The locked cross-hair cursor will appear double-lined. To unlock the cursor, click again. Click 'Hide Grids' to hide the grids and cross-hair cursor. By not showing all the graphical elements in a heat map, the visual rendering is faster.