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HitWalker2: visual analytics for precision medicine and beyond.

Daniel Bottomly1, Shannon K McWeeney2, Beth Wilmot2

  • 1Knight Cancer Institute, Oregon Clinical and Translational Research Institute and.

Bioinformatics (Oxford, England)
|December 29, 2015
PubMed
Summary
This summary is machine-generated.

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HitWalker2 offers a flexible, web-based tool for data visualization and interpretation in precision medicine and systems genetics. This interactive approach aids discovery across diverse research areas like cancer and psychiatric disorders.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Lack of visualization frameworks hinders interpretation and discovery in precision medicine and systems genetics.
  • Existing tools may not be flexible enough for diverse data types and research questions.

Purpose of the Study:

  • To develop an interactive, reproducible, web-based prioritization approach for data analysis.
  • To create a flexible tool, HitWalker2, that supports various data types and prioritization methods.

Main Methods:

  • HitWalker2 is built using Python/Django, Neo4j, and Javascript (D3.js, jQuery).
  • It provides an interactive and reproducible web-based platform.
  • The approach is designed for flexibility, accommodating diverse data and research questions.

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Main Results:

  • HitWalker2 facilitates interpretation and discovery in complex biological studies.
  • The tool is applicable to a wide range of research areas, including cancer, infectious disease, and psychiatric disorders.
  • It enhances the analysis of precision medicine and systems genetics data.

Conclusions:

  • HitWalker2 addresses the bottleneck of data visualization in complex biological research.
  • Its flexibility and interactive nature make it a valuable tool for diverse scientific studies.
  • The open-source availability promotes reproducibility and wider adoption in the scientific community.