Inferring modulators of genetic interactions with epistatic nested effects models.
Maps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in differ...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2017-04-01
|
| Series: | PLoS Computational Biology |
| Online Access: | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005496&type=printable |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849472154857373696 |
|---|---|
| author | Martin Pirkl Madeline Diekmann Marlies van der Wees Niko Beerenwinkel Holger Fröhlich Florian Markowetz |
| author_facet | Martin Pirkl Madeline Diekmann Marlies van der Wees Niko Beerenwinkel Holger Fröhlich Florian Markowetz |
| author_sort | Martin Pirkl |
| collection | DOAJ |
| description | Maps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in different ways (called mixed epistasis). Here we test the hypothesis that mixed epistasis between a gene pair can be explained by the action of a third gene that modulates the interaction. We have extended the framework of Nested Effects Models (NEMs), a type of graphical model specifically tailored to analyze high-dimensional gene perturbation data, to incorporate logical functions that describe interactions between regulators on downstream genes and proteins. We benchmark our approach in the controlled setting of a simulation study and show high accuracy in inferring the correct model. In an application to data from deletion mutants of kinases and phosphatases in S. cerevisiae we show that epistatic NEMs can point to modulators of genetic interactions. Our approach is implemented in the R-package 'epiNEM' available from https://github.com/cbg-ethz/epiNEM and https://bioconductor.org/packages/epiNEM/. |
| format | Article |
| id | doaj-art-f2da76bcbacf4d0faea151c40ce313db |
| institution | Kabale University |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2017-04-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-f2da76bcbacf4d0faea151c40ce313db2025-08-20T03:24:36ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582017-04-01134e100549610.1371/journal.pcbi.1005496Inferring modulators of genetic interactions with epistatic nested effects models.Martin PirklMadeline DiekmannMarlies van der WeesNiko BeerenwinkelHolger FröhlichFlorian MarkowetzMaps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in different ways (called mixed epistasis). Here we test the hypothesis that mixed epistasis between a gene pair can be explained by the action of a third gene that modulates the interaction. We have extended the framework of Nested Effects Models (NEMs), a type of graphical model specifically tailored to analyze high-dimensional gene perturbation data, to incorporate logical functions that describe interactions between regulators on downstream genes and proteins. We benchmark our approach in the controlled setting of a simulation study and show high accuracy in inferring the correct model. In an application to data from deletion mutants of kinases and phosphatases in S. cerevisiae we show that epistatic NEMs can point to modulators of genetic interactions. Our approach is implemented in the R-package 'epiNEM' available from https://github.com/cbg-ethz/epiNEM and https://bioconductor.org/packages/epiNEM/.https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005496&type=printable |
| spellingShingle | Martin Pirkl Madeline Diekmann Marlies van der Wees Niko Beerenwinkel Holger Fröhlich Florian Markowetz Inferring modulators of genetic interactions with epistatic nested effects models. PLoS Computational Biology |
| title | Inferring modulators of genetic interactions with epistatic nested effects models. |
| title_full | Inferring modulators of genetic interactions with epistatic nested effects models. |
| title_fullStr | Inferring modulators of genetic interactions with epistatic nested effects models. |
| title_full_unstemmed | Inferring modulators of genetic interactions with epistatic nested effects models. |
| title_short | Inferring modulators of genetic interactions with epistatic nested effects models. |
| title_sort | inferring modulators of genetic interactions with epistatic nested effects models |
| url | https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005496&type=printable |
| work_keys_str_mv | AT martinpirkl inferringmodulatorsofgeneticinteractionswithepistaticnestedeffectsmodels AT madelinediekmann inferringmodulatorsofgeneticinteractionswithepistaticnestedeffectsmodels AT marliesvanderwees inferringmodulatorsofgeneticinteractionswithepistaticnestedeffectsmodels AT nikobeerenwinkel inferringmodulatorsofgeneticinteractionswithepistaticnestedeffectsmodels AT holgerfrohlich inferringmodulatorsofgeneticinteractionswithepistaticnestedeffectsmodels AT florianmarkowetz inferringmodulatorsofgeneticinteractionswithepistaticnestedeffectsmodels |