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Electronic notebook for "Deep reefs are not universal refuges: reseeding potential varies among coral species" (Science Advances, 2017)

Home Page: http://advances.sciencemag.org/content/3/2/e1602373

Python 51.44% R 47.87% Shell 0.69%
radseq coral symbiodinium electronic-notebooks python

bermuda-rad's Introduction

"Deep reefs are not universal refuges: reseeding potential varies among coral species"

Manuscript reference: Bongaerts P, Riginos C, Brunner R, Englebert N, Smith SR, Hoegh-Guldberg O (2016) Deep reefs are not universal refuges: reseeding potential varies among coral species. Science Advances 3:e1602373 [DOI: 10.1126/sciadv.1602373]

Electronic lab notebook author: Pim Bongaerts

Manuscript

Electronic lab notebook contents

A - Symbiodinium - Details the analysis of the sequence data for the FACS-isolated Symbiodinium that are used as subtraction datasets.

B - Agaricia - Details the processing and analyses of the Agaricia fragilis dataset, from raw sequences to eventual population genomic analyses.

C - Stephanocoenia - Details the processing and analyses of the Stephanocoenia intersepta dataset, from raw sequences to eventual population genomic analyses.

D - Figures - Contains the data and scripts to produce the manuscript figures.

E - Scripts - Several custom scripts (other than those in RADseq script library) specific to the analysis of the Bermuda dataset.

F - Protocols - Details the lab protocols for gDNA isolation and fluorescence-activated cell sorting.

Additional resources

Raw sequence data (NCBI SRA) - Raw Illumina sequence data (fastq format) for the 109 Stephanocoenia intersepta and 104 Agaricia fragilis coral colonies sequenced in this study (accession code PRJNA361144).

RADseq script library (GitHub) - Separate github repository with generic Python scripts used throughout the electronic lab notebook (A-C).

Fieldwork Photos (Gallery) - Several photos of the fieldwork in Bermuda

Explanation

Each (sub)heading in the electronic notebooks (listed above) refers to a directory in the repository, outlining the analysis workflow in sequential order.

Screenshot

Files are marked with a code referring to the directory/step where they were generated. In the example below, the input file afra_2b.vcf was produced in the step/directory B2b - Basic SNP QC and filtering, and the output file of this step/directory B2c - Check for clones is labeled afra_2c.vcf.

Screenshot

Software and dependencies

Besides the Python scripts in the separate RAD - Python scripts repository, the analyses depend on the following packages that need to be accessible through the PATH environmental variable:

Package Version (used) Type Note
PyRAD 3.0.6 Python Application requires: numpy, scipy, muscle and vsearch
PyVCF 0.6.7 Python Module
NumPy 1.11.1 Python Package
BioPython 1.67 Python Package
vcfR 1.2.0 R Package
hierfstat 0.04-22 R Package
adegenet 2.0.1 R Package
BLAST+ 2.5.0 Executable (CL) (older versions no longer support remote db connect)
VCFtools 0.1.15 Executable (CL)
PGDSpider 2.0.5.1 Executable (CL/GUI) used with a command-line wrapper
Arlecore 3.5.2.2 Executable (CL) part of Arlequin package
Lositan 1.0.0 Executable (GUI)
BayeScan 2.1 Executable (CL)
STRUCTURE 2.3.4 Executable (CL/GUI) used with a multi-threading wrapper

Additional R packages used for plotting [figures](D - Figures/README.md): ggplot2, reshape2, gridExtra, cowplot, plyr

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