GEO DataSets

(Submitter supplied) An important goal in disease genetics and evolutionary biology is to understand how mutations combine together to alter phenotypes and fitness.  Non-additive genetic (epistatic) interactions between mutations occur extensively within and between genes, which makes accurate genetic prediction a difficult challenge.  Moreover, for unclear reasons, the interactions between mutations change quite extensively across conditions, cell types, and species, with important consequences for both evolution and precision medicine such as the exploitation of synthetic lethality in cancer. To better understand the plasticity of genetic interactions, we reduced the problem to a minimal system where we combined mutations within a single protein performing a single cellular function. more...

Organism:

synthetic construct

Type:

Other

Platform:

GPL19604

18 Samples

Download data: TXT

(Submitter supplied) We construced combinations of genetic deletions to infer genetic interactions in genomic expression data. Keywords: combinatorial genetic perturbations

Organism:

Saccharomyces cerevisiae

Type:

Expression profiling by array

Platforms:

GPL90 GPL2622

90 Samples

Download data

(Submitter supplied) Contains gene expression profiles of yeast single and double deletion mutants of gene-specific transcription factors. Genetic interactions were studied by comparing gene expression changes of double mutants with gene expression changes in the respective single mutants. Pairs of gene-specific transcription factors were chosen based on previous evidence for epistasis, including synthetic genetic interactions as well as common DNA binding.

Organism:

Saccharomyces cerevisiae

Type:

Expression profiling by array

Platform:

GPL11232

287 Samples

Download data: TXT