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Analysis code and scripts for the Aquaponics collab with Jessica Day et. al.

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🐟 🌱 🎉 ISB Aquaponics

Analysis code and scripts for the Aquaponics project with Jessica Day et. al. available as:

Negative plant-microbiome feedback limits productivity in aquaponics
Jessica A Day, Anne E Otwell, Christian Diener, Kourtney E Tams, Brad M Bebout, Angela M Detweiler, Michael D Lee, Madeline T Scott, Wilson Ta, Monica Ha, Shienna A Carreon, Kenny Tong, Abdirizak A Ali, Sean M Gibbons, Nitin S Baliga
https://doi.org/10.1101/709162

Ask questions or report issues at https://github.com/gibbons-lab/aquaponics/issues.

Install required software

We currently only support setups on MacOS or Linux. You will need R (installation instructions), Rstudio (installation instructions) and minimap2. To install minimap2 we recommend using miniconda which allows you to install minimap2 with:

conda install -c bioconda minimap2

All analysis is performed by mbtools. To install this package open your R console and use

install.packages(c("BiocManager", "remotes"))
setRepositories(ind=1:2)
remotes::install_github("gibbons-lab/mbtools")

Reproduce the study

0. Download or clone the repository.

You can download the repository using the green Clone or download on the top right. Alternatively you can use git to clone the repository:

git clone https://github.com/gibbons-lab/aquaponics

1. Download the data and SILVA DB

Coming soon
This is not required to reproduce the next steps since a final abundance tables have already been placed in data.

2. Align full-length reads to the SILVA and database and count with the EM algorithm

Again not required for the next steps. Everything is performed after downloading the data and SILVA DB and running the align.R script. Note that this will require large amounts of memory (~100GB) and several cores to be efficient. In case you have less memory set limited_memory = TRUE in the align.R script. The number of used threads will be inferred from mc.cores option in R. You can set it before running the script. For instance by using

Rscript -e "options(mc.cores = 10); source('align.R')"

3. Reproduce study analyses

Each of the following steps can be run individually and out of order and will reproduce the figures found in the manuscript. To reproduce the steps open the top level of this repository and open any of the *.rmd files mentioned below. The output of each step is linked as well.

Nanopore benchmarks

Please see the nanopore_benchmark directory for details.

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