How to Examine Pathways in Next Generation Clustered Heat Maps

In this article, we will use the Pathways Tool to investigate the pathways related to gene-expression patterns in a Next-Generation Clustered Heat Map (NG-CHM). Specifically, we will explore our TCGA THYM rnaSEQ gene by sample map. The samples in this map have been grouped into four clusters based on hierarchical gene-expression clustering, as shown in the top covariate bar.

How to Create Next-Generation Clustered Heat Maps with the Interactive Builder

Updated: August 7, 2018 and August 27, 2018. This article illustrates how to create a Next-Generation Clustered Heat Map (NG-CHM) using our web-based interactive builder. The web-based interactive builder is suitable for building small to moderate sized single maps (at most a few thousand elements on any axis). If you want to build larger maps, or build a suite of maps programmatically, our Galaxy- or R-based environments are more suitable.

Linkout Type Descriptions

Link-outs in NG-CHMs are determined by assigning types to the row and column labels in a heat map. Plugins installed in the heat map viewer provide link-outs to appropriate resources for matching types.

A database describing in detail the available label types is under development.

As an interim measure this page lists the label types recognized by the standard NG-CHM plugins.


Clustered Heat Maps for Big Data

Interactive, highly-responsive “Next-Generation” Clustered Heat Maps (NG-CHMs) are ideal for exploring heat maps of big data. NG-CHMs enable the user to zoom and navigate dynamically and link out to dozens of external data resources and tools. NG-CHMs exploit recent advances in web technology to improve performance, provide a highly-responsive user experience, and facilitate deep exploration of the biology (or other science) behind the image.

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