Cookie Settings

We use cookies to optimize our website. These include cookies that are necessary for the operation of the site, as well as those that are only used for anonymous statistic. You can decide for yourself which categories you want to allow. Further information can be found in our data privacy protection .


These cookies are necessary to run the core functionalities of this website and cannot be disabled.

Name Webedition CMS
Purpose This cookie is required by the CMS (Content Management System) Webedition for the system to function correctly. Typically, this cookie is deleted when the browser is closed.
Name econda
Purpose Session cookie emos_jcsid for the web analysis software econda. This runs in the “anonymized measurement” mode. There is no personal reference. As soon as the user leaves the site, tracking is ended and all data in the browser are automatically deleted.

These cookies help us understand how visitors interact with our website by collecting and analyzing information anonymously. Depending on the tool, one or more cookies are set by the provider.

Name econda
Purpose Statistics
External media

Content from external media platforms is blocked by default. If cookies from external media are accepted, access to this content no longer requires manual consent.

Name YouTube
Purpose Show YouTube content
Name Twitter
Purpose activate Twitter Feeds

Miscellaneous tools

Open-source toolkit for analyzing and visualizing challenge results

ChallengeR is an R package for analyzing and visualizing challenge results in the field of biomedical image analysis and beyond intuitive way to gain important insights into the relative and absolute performance of algorithms.
For details see:
Wiesenfarth M, Reinke A, Landman BA, Eisenmann M, Saiz LA, Cardoso MJ, Maier-Hein L, Kopp-Schneider A. Methods and open-source toolkit for analyzing and visualizing challenge results. Sci Rep. 2021 Jan 27;11(1):2369. Doi: 10.1038/s41598-021-82017-6.


Cochran-Armitage Test for trend
The WebApp CATrend computes the one-sided p-values of the Cochran-Armitage trend test for the asymptotic and the exact conditional test. The Cochran-Armitage Test for trend is used in the analysis of 2 x k contingency tables with k ordered categories. It compares the null hypothesis of equal proportions in all k categories to the alternative of ordered proportions. Details, also about numerical calculation can be found in the WebApp. A corresponding R package (CATTexact) is available.


Clustering and visualization of mixed-type data
CluMix is an R package that provides utilities for clustering subjects and variables with mixed data types. The main feature is the creation of a mixed-data heatmap.
For details see:
Hummel M, Edelmann D, Kopp-Schneider A. Clustering of samples and variables with mixed-type data. PLoS One. 2017 Nov 28;12(11):e0188274. doi: 10.1371/journal.pone.0188274. eCollection 2017.


Visual analytics for the integrated analysis of microarray data
SEURAT provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data. Gene expression data can be analyzed together with associated clinical data, array CGH (comparative genomic hybridization), SNP array (single nucleotide polymorphism) data and available gene annotations in an integrated manner.
For details see:
Gribov A*, Sill M*, Lück S, Rücker F, Döhner K, Bullinger L, Benner A, Unwin A (2010). SEURAT: visual analytics for the integrated analysis of microarray data. BMC Med Genomics;3:21. (* joint first authors). DOI: 10.1186/1755-8794-3-21


Biclustering via sparse singular value decomposition incorporating stability selection
s4vd is an addon package for the R-package biclust and provides implementations of the ssvd and s4vd algorithm to perform biclustering via sparse singular value decomposition with and without stability selection.
For details see:
Sill M, Kaiser S, Benner A and Kopp-Schneider A (2011). Robust biclustering by sparse singular value decomposition incorporating stability selection. Bioinformatics 27(15) 2089-2097. DOI:10.1093/bioinformatics/btr322

to top
powered by webEdition CMS