eprintid: 26397
rev_number: 13
eprint_status: archive
userid: 1589
dir: disk0/00/02/63/97
datestamp: 2019-07-24 13:02:58
lastmod: 2019-08-12 11:59:08
status_changed: 2019-07-24 13:02:58
type: article
metadata_visibility: show
creators_name: Urpa, Lea M.
creators_name: Anders, Simon
title: Focused multidimensional scaling: interactive visualization for exploration of high-dimensional data
subjects: ddc-570
divisions: i-706000
keywords: Clustering, High-dimensional data, Visualization, Personalized medicine
abstract: Background: Visualization is an important tool for generating meaning from scientific data, but the visualization of structures in high-dimensional data (such as from high-throughput assays) presents unique challenges. Dimension reduction methods are key in solving this challenge, but these methods can be misleading- especially when apparent clustering in the dimension-reducing representation is used as the basis for reasoning about relationships within the data.

Results: We present two interactive visualization tools, distnet and focusedMDS, that help in assessing the validity of a dimension-reducing plot and in interactively exploring relationships between objects in the data. The distnet tool is used to examine discrepancies between the placement of points in a two dimensional visualization and the points’ actual similarities in feature space. The focusedMDS tool is an intuitive, interactive multidimensional scaling tool that is useful for exploring the relationships of one particular data point to the others, that might be useful in a personalized medicine framework.

Conclusions: We introduce here two freely available tools for visually exploring and verifying the validity of dimension-reducing visualizations and biological information gained from these. The use of such tools can confirm that conclusions drawn from dimension-reducing visualizations are not simply artifacts of the visualization method, but are real biological insights.
date: 2019
publisher: BioMed Central ; Springer
id_scheme: DOI
ppn_swb: 1671169492
own_urn: urn:nbn:de:bsz:16-heidok-263976
language: eng
bibsort: URPALEAMFOCUSEDMUL2019
full_text_status: public
publication: BMC Bioinformatics
volume: 20
number: 221
place_of_pub: London ; Berlin, Heidelberg
pagerange: 1-8
issn: 1471-2105
citation:   Urpa, Lea M. ; Anders, Simon  (2019) Focused multidimensional scaling: interactive visualization for exploration of high-dimensional data.  BMC Bioinformatics, 20 (221).  pp. 1-8.  ISSN 1471-2105     
document_url: https://archiv.ub.uni-heidelberg.de/volltextserver/26397/1/12859_2019_Article_2780.pdf