Code and data for analysis described in the manuscript: "Design of synthetic bacterial communities for predicable plant phenotypes".
This is an R package that is distributed with the aim on ensuring reproducibility. The code was designed and tested to work specifically with the data in the package.
For the code that fits the neural network visit our sister repository wheelPi.
You will require the devtools package. Once that package is installed just type:
devtools::install_github("surh/wheelP")The raw sequence data is available in the appropriate academic repositories. RNA-seq data is at NCBI GEO database under accession GSE102248. Microbial 16S gene sequencing is available at the EBI SRA under accession PRJEB22060.
All other experimental data and numeric values underlying figures in the associated manuscript
is made available here as R package data. It can be accessed after installation using
data(<DATASETNAME>) in the R console. A full description of all the available
datasets can be found at the DATASETS.md file.
The scripts directory contains scripts used for analysis in the associated manuscript. The scripts follow a naming convention in which a prefix is used to indicate the general set of data that they analyze, and they are numbered to indicate they way in which they were run. In some cases, scripts with higher numbers are dependent on output from scripts with lower numbers. The prefixes are as follow:
- gc_ corresponds to the analysis of in vitro bacterial growth curves.
- binP_ corresponds to the analysis of plant phenotypes in plant-bacterium binary interaction assays.
- syncom_ corresponds to the analysis of plant phenotypes in bacterial synthetic community assays.
- colonization_ corresponds to the analysis of bacterial abundances in synthetic community assays.
- rna_ corresponds to the analysis of plant transcriptomes in synthetic community assays.
If using the code or data, please reference this repository's URL, as well as the following:
*Herrera Paredes S, *Gao T, Law TF, Finkel OM, Mucyn T, Texeira PJPL, Salas González I, Feltcher ME, Powers MJ, Shank EA, Jones CD, Jojic V, Dangl JL & Castrillo G. "Design of synthetic bacterial communities for predicable plant phenotypes" (2017). *In press. doi: 10.1371/journal.pbio.2003962. *Co-first authors.
(C) Copyright 2017 Sur Herrera Paredes
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