Urban biogeography of fungal endophytes across San Francisco

Repository of the code, data, and text for the manuscript "Urban biogeography of fungal endophytes across San Francisco" published in the scientific journal PeerJ, written by Emma Gibson and Naupaka Zimmerman.

Use of Google Maps images follows the guidelines here:
https://about.google/brand-resource-center/products-and-services/geo-guidelines/

Steps to reproduce the analyses and generate the manuscript

1. You'll need to install Docker and git first if you don't have them already.
2. Then, clone the repository, build the image, and start a container with RStudio server.

git clone https://github.com/ZimmermanLab/SF-metrosideros-endophytes
cd SF-metrosideros-endophytes
docker build -t sfendos . 
docker run --rm -d -p 8787:8787 -e DISABLE_AUTH=true -e ROOT=true -v /home/rstudio/sfendos/renv sfendos

OR, if you have docker installed and want to use the prebuilt image from Docker Hub, it's even easier/faster:

docker run --rm -d -p 8787:8787 -e DISABLE_AUTH=true -e ROOT=true -v /home/rstudio/sfendos/renv naupaka/sfendos

3. Open http://localhost:8787 in your web browser.
4. Click on the sfendos directory in the file pane (lower right of the window), and then on the SF-metrosideros-endophytes.Rproj file to open the project.
5. Open a new bash terminal in the RStudio Server interface and type make.
6. Go get a cup of coffee (it still has to install a good number of LaTeX packages) and when you come back the manuscript should be built..

Overview of files and directory structure

The directory structure is shown below. The most important files are the raw data in the data/ directory, the gibson2023.Rmd Rmarkdown file that contains all of the text and a good bit of the code for the manuscript, the references.bib file that contains the references for the manuscript, and the scripts in the scripts/ directory, which are called by the Rmd file or the Makefile to run the pipeline. The computational environment is specified by the Dockerfile and the renv.lock file. The output/ directory contains a number of intermediate output files for the processing pipeline, and also includes the R session info for the last time the manuscript was generated, in output/log_files/r_session_info.txt. Other files that haven't been mentioned are mostly ancillary files for generating the manuscript using bookdown and LaTeX.

├── Dockerfile
├── LICENSE.md
├── Makefile
├── README.md
├── SF-metrosideros-endophytes.Rproj
├── data
│   ├── blast_results_for_unknowns
│   │   ├── EUSF00620-genbank-blastn-alignment-2021-10-31.txt
│   │   └── EUSF00664-genbank-blastn-alignment-2021-10-31.txt
│   ├── metadata
│   │   ├── culturing_worksheet_emma.csv
│   │   ├── extraction_worksheet_emma.csv
│   │   ├── m_excel_tree_metadata_with_isolationfreq.csv
│   │   ├── tbas_taxonomies.csv
│   │   └── water_voucher_worksheet_emma.csv
│   └── sequences
│       ├── hand-cleaned_seqs
│       └── new_zealand_sequence_search.csv
├── gibson2023.Rmd
├── gibson2023.fff
├── gibson2023.log
├── gibson2023.pdf
├── gibson2023.tex
├── gibson2023.ttt
├── gibson2023_files
│   └── figure-latex
│       ├── isolation-dbh-freq-plots-1.pdf
│       ├── nmds-plot-1.pdf
│       ├── rarefaction-plot-1.pdf
│       ├── site-map-1.pdf
│       └── taxonomy-by-site-plot-1.pdf
├── init_docker.sh
├── output
│   ├── log_files
│   │   ├── r_session_info.txt
│   │   └── seq_script_log.txt
│   ├── metadata_tables
│   │   ├── groupfile.tsv
│   │   ├── m_excel_tree_metadata_with_isolationfreq_wgs_lat_long.csv
│   │   └── tbas_with_site.csv
│   ├── mothur_pipeline
│   │   ├── 01_all_seqs.fasta
│   │   ├── 02_good_seqs.fasta
│   │   ├── 04_good_seqs_short_names_checked.agc.0.03.fasta
│   │   ├── 04_good_seqs_short_names_checked.agc.list
│   │   ├── 04_good_seqs_short_names_checked.count_table
│   │   ├── 04_good_seqs_short_names_checked.fasta
│   │   ├── 04_good_seqs_short_names_checked.names
│   │   ├── 04_good_seqs_short_names_checked.unique.fasta
│   │   ├── 05_seq_names.txt
│   │   ├── 06_otu_temp.txt
│   │   ├── 07_seq_ids_temp.txt
│   │   ├── 08_seq_with_OTU_ID.txt
│   │   ├── 09_otu_seq_sorted.txt
│   │   ├── 10_names_sorted.txt
│   │   ├── 11_joined_otu_seqs.txt
│   │   └── 12_seq_with_OTU_ID.txt
│   ├── sf_basemap.Rdata
│   └── tbas_output
│       ├── 2019-06-17_tbas21_archiveYIYORC5W_.tar.gz
│       └── 2019-06-17_tbas_run
├── peerj.csl
├── preamble.tex
├── references.bib
├── renv
│   ├── activate.R
│   └── settings.dcf
├── renv.lock
├── scripts
│   ├── 01_process_fasta.sh
│   ├── 02_join_metadata.R
│   ├── 03_make_otu_table.R
│   ├── 04_clean_and_join_tbas_taxonomy.R
│   └── 05_setup_maps_and_gis_coords.R
└── wlpeerj.cls

16 directories, 60 files