Change search
ReferencesLink to record
Permanent link

Direct link
Statistical Assessment of Crosstalk Enrichment between Gene Groups in Biological Networks
KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
2013 (English)In: PLoS ONE, ISSN 1932-6203, Vol. 8, no 1, e54945- p.Article in journal (Refereed) Published
Abstract [en]

Motivation: Analyzing groups of functionally coupled genes or proteins in the context of global interaction networks has become an important aspect of bioinformatic investigations. Assessing the statistical significance of crosstalk enrichment between or within groups of genes can be a valuable tool for functional annotation of experimental gene sets. Results: Here we present CrossTalkZ, a statistical method and software to assess the significance of crosstalk enrichment between pairs of gene or protein groups in large biological networks. We demonstrate that the standard z-score is generally an appropriate and unbiased statistic. We further evaluate the ability of four different methods to reliably recover crosstalk within known biological pathways. We conclude that the methods preserving the second-order topological network properties perform best. Finally, we show how CrossTalkZ can be used to annotate experimental gene sets using known pathway annotations and that its performance at this task is superior to gene enrichment analysis (GEA). Availability and Implementation: CrossTalkZ (available at is implemented in C++, easy to use, fast, accepts various input file formats, and produces a number of statistics. These include z-score, p-value, false discovery rate, and a test of normality for the null distributions.

Place, publisher, year, edition, pages
2013. Vol. 8, no 1, e54945- p.
Keyword [en]
Expression Profiles, Pathway, Genome, Cancer, False
National Category
Biological Sciences
URN: urn:nbn:se:kth:diva-118180DOI: 10.1371/journal.pone.0054945ISI: 000314021500148ScopusID: 2-s2.0-84872806763OAI: diva2:605263
Science for Life Laboratory - a national resource center for high-throughput molecular bioscienceSwedish Research Council

QC 20130213

Available from: 2013-02-13 Created: 2013-02-13 Last updated: 2013-03-08Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Alexeyenko, Andrey
By organisation
Gene TechnologyScience for Life Laboratory, SciLifeLab
In the same journal
Biological Sciences

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 26 hits
ReferencesLink to record
Permanent link

Direct link