Dataset Information
Incorporating interaction networks into the determination of functionally related hit genes in genomic experiments with Markov random fields.
Ontology highlight
ABSTRACT: Motivation
Incorporating gene interaction data into the identification of 'hit' genes in genomic experiments is a well-established approach leveraging the 'guilt by association' assumption to obtain a network based hit list of functionally related genes. We aim to develop a method to allow for multivariate gene scores and multiple hit labels in order to extend the analysis of genomic screening data within such an approach.Results
We propose a Markov random field-based method to achieve our aim and show that the particular advantages of our method compared with those currently used lead to new insights in previously analysed data as well as for our own motivating data. Our method additionally achieves the best performance in an independent simulation experiment. The real data applications we consider comprise of a survival analysis and differential expression experiment and a cell-based RNA interference functional screen.Availability and implementation
We provide all of the data and code related to the results in the paper.Contact
sean.j.robinson@utu.fi or laurent.guyon@cea.fr.Supplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Robinson S
PROVIDER: S-EPMC5870666 | biostudies-literature | 2017 Jul
REPOSITORIES: biostudies-literature
Publications
Incorporating interaction networks into the determination of functionally related hit genes in genomic experiments with Markov random fields.
Bioinformatics (Oxford, England) 20170701 14
<h4>Motivation</h4>Incorporating gene interaction data into the identification of 'hit' genes in genomic experiments is a well-established approach leveraging the 'guilt by association' assumption to obtain a network based hit list of functionally related genes. We aim to develop a method to allow for multivariate gene scores and multiple hit labels in order to extend the analysis of genomic screening data within such an approach.<h4>Results</h4>We propose a Markov random field-based method to a ...[more]