Format

Send to

Choose Destination
Bioinformatics. 2019 Jan 18. doi: 10.1093/bioinformatics/btz021. [Epub ahead of print]

METACLUSTER - an R package for context-specific expression analysis of metabolic gene clusters.

Author information

1
Department of Plant Biology, Carnegie Institution for Science, Stanford, USA.
2
Max Planck Institute for Plant Breeding Research, Cologne, Germany.

Abstract

Plants and microbes produce numerous compounds to cope with their environments but the biosynthetic pathways for most of these compounds have yet to be elucidated. Some biosynthetic pathways are encoded by enzymes collocated in the chromosome. To facilitate a more comprehensive condition and tissue-specific expression analysis of metabolic gene clusters, we developed METACLUSTER, a probabilistic framework for characterizing metabolic gene clusters using context-specific gene expression information.

Availability:

METACLUSTER is freely available at https://github.com/mbanf/METACLUSTER.

Supplementary information:

Supplementary methods and data are available at Bioinformatics online.

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center