DOI: 10.5061/dryad.gxd2547zf
title: Dataset for distinct microbiomes of the scleractinian coral <em>Favia fragum</em> in mangrove and adjacent reef habitats in the Panamanian Caribbean

description: This dataset supports a manuscript examining microbial communities
 associated with the scleractinian coral Favia fragum across mangrove and
 adjacent reef habitats in the Panamanian Caribbean. The dataset includes
 the complete analytical workflow and scripts used to process, analyze, and
 visualize 16S rDNA amplicon sequencing data from coral-associated
 microbiomes. Demultiplexed amplicon libraries were analyzed in RStudio
 using the DADA2 pipeline, followed by community-level statistical analyses
 and visualizations. A finalized phyloseq object is provided, containing
 all sequences, taxonomy, and metadata necessary to reproduce statistical
 tests and graphical outputs. All scripts required to replicate the
 analyses are included, along with PDF versions of the R code. Trimmed and
 demultiplexed sequencing reads are publicly available through the NCBI
 Sequence Read Archive under BioProject PRJNA1023296.
description: # Dataset for distinct microbiomes of the scleractinian coral *Favia
 fragum* in mangrove and adjacent reef habitats in the Panamanian Caribbean
 This material is based upon work supported by the National Science
 Foundation under Grant Nos. EF-2025121, EF-2025067, EF-2025009, and
 EF-2150107. Any opinions, findings, and conclusions or recommendations
 expressed in this material are those of the author(s) and do not
 necessarily reflect the views of the National Science Foundation. ####
 Description of the data and file structure *
 Favia_Demultiplexing_and_trimming.txt: A generic and customizable workflow
 (text script) for demultiplexing and trimming raw Illumina MiSeq
 sequencing files. This script is provided for users to apply to their own
 raw sequencing data and to understand the initial processing steps that
 lead to demultiplexed reads. * Favia_workflow_dada2_to_phyloseq.R: An R
 script to implement the DADA2 pipeline for amplicon analysis, generating a
 phyloseq object from demultiplexed reads. * Favia.ps.RDS: A pre-computed
 phyloseq object in R's RDS format, representing the final processed
 amplicon dataset. The R Package 'phyloseq' will be required to
 download and utilize this object. *
 Favia_workflow_phyloseq_analysis_visualization.R: An R script for
 analyzing community data, performing statistical tests, and generating
 visualizations from a phyloseq object. * Favia.ps.RDS: precomputed
 phyloseq object from the outputs of DADA2 and the metadata file
 "Favia_metadata_2.csv." * favia_metadata_2.csv: metadata file to
 incorporate into phyloseq object. * sample\ Unique identifier for each
 measured sample or site (e.g., CC01, CK03). * site\ General location where
 the sample was collected (e.g., Coral Key, STRI). * habitat\ Type of
 environment where the sample occurs, such as a reef or mangrove. * length\
 Maximum length of the sampled feature or structure (typically in
 centimeters). * width\ Maximum width of the sampled feature (typically in
 centimeters). * height\ Vertical dimension or thickness of the sampled
 feature (typically in centimeters). * surf.area (surface area)\ Total
 surface area of the sampled feature, usually calculated from length,
 width, and height (typically in square centimeters). * lat (latitude)\
 Geographic latitude of the sampling location, expressed in decimal
 degrees. * long (longitude)\ Geographic longitude of the sampling
 location, expressed in decimal degrees. Getting Started Demultiplexing and
 Trimming Your Own Raw Data (Informational Only for this Dataset) While the
 raw sequencing files for this specific study are not included here, we
 provide the Favia_demultiplex_trim_workflow.txt script as a generic guide
 for demultiplexing and trimming Illumina MiSeq raw data. This workflow
 outlines the steps that produce demultiplexed Read 1 and Read 2 files per
 sample, consistent with the format of the files available on SRA for this
 study. You can use this script to process your own raw sequencing data or
 to understand the initial steps taken in similar amplicon sequencing
 pipelines. 1. Download Raw Data: Obtain your raw Illumina MiSeq sequencing
 files (e.g., FASTQ files). 2. Demultiplexing and Trimming Workflow: * Open
 and customize the Favia_demultiplex_trim_workflow.txt script. * This
 workflow requires the Perl script "MergeMeCheck3.pl". This
 script is available on our GitHub website:
 [https://marineinvert.github.io/microbiome/resources.html](https://marineinvert.github.io/microbiome/resources.html). Please download MergeMeCheck3.pl and place it in an accessible directory. * Execute the steps outlined in Favia_demultiplex_trim_workflow.txt using your preferred command-line environment. 3. Outputs: The output of this workflow will be demultiplexed Read 1 and Read 2 FASTQ files for each sample, along with statistics from the demultiplexing and trimming steps. Users have two primary options for working with this dataset: 1. Start from demultiplexed files (downloaded from SRA): Use the demultiplexed Read 1 and Read 2 files from SRA as the input for the DADA2 pipeline. 2. Start from the supplied phyloseq object: Directly use the pre-computed Favia.ps.RDS phyloseq object for downstream community analyses. Amplicon Analysis with DADA2 (from Demultiplexed Files) The demultiplexed Read 1 and Read 2 files for this study are available in the Sequence Read Archive (SRA) under Submission #SUB13878240 for BioProject #PRJNA1023296. If you have downloaded these files, you can proceed with ASV inference using DADA2: * Download Demultiplexed Files: Obtain the demultiplexed Read 1 and Read 2 FASTQ files for each sample from SRA (BioProject #PRJNA1023296, Submission #SUB13878240). * Download and install R and RStudio: Ensure you have a recent version of R and RStudio installed. * Install Required R Packages: Open RStudio and install the necessary packages, particularly dada2 and phyloseq. * Run Favia_workflow_dada2_to_phyloseq.R: * Open the Favia_workflow_dada2_to_phyloseq.R script in RStudio. * Download the Favia_metadata_2.csv table containing the metadata for each sample and save it into an accessible directory. * Modify the file paths within the script to point to your downloaded demultiplexed Read 1 and Read 2 FASTQ files. * Run the script. This script implements the DADA2 pipeline, including quality filtering, dereplication, ASV inference, chimera removal, and taxonomic assignment. * Outputs of DADA2: The script will generate a phyloseq object. This object encapsulates: * ASV Table: A matrix of amplicon sequence variants (ASVs) by samples, containing the abundance of each ASV in each sample. * Taxonomy Table: A table assigning taxonomic classifications (e.g., Kingdom, Phylum, Class, Order, Family, Genus, Species) to each ASV. * Sample Data: A data frame containing metadata for each sample (e.g., experimental conditions, sampling location, etc.). * Phylogenetic Tree (Optional): Depending on the specific DADA2 pipeline implementation, a phylogenetic tree relating the ASVs may also be included. Community Analysis and Visualization (from Phyloseq Object) You can either use the phyloseq object generated from the previous step or directly use the supplied Favia.ps.RDS file to perform downstream analyses: * Load Phyloseq Object: * If you generated your own phyloseq object, it will be in your R environment. * If using the supplied object, load it into R using readRDS("Favia.ps.RDS"). * Run Favia_workflow_phyloseq_analysis_visualization.R: * Open the Favia_workflow_phyloseq_analysis_visualization.R script in RStudio. * Run the script to reproduce the analyses and visualizations.