Code and data from the publication Genetic and functional variation across regional and local scales is associated with climate in a foundational prairie grass
├── app.R
This code produces the Shiny app dashboard for visualizing genetic diversity in blue grama grass. Several options can be set, including:
- Number of principal components - this is a parameter for DAPC fitting. One must avoid overfitting with too many principal components. Around 60 is typically the optimal number for Regional or State level groupings. However, it is important to cross validate to determine the exact optimal number for final analysis.
- Populations to include
- Level of grouping across which to detect variance (i.e., Site level, Regional level, or State level)
Current terminal usage should be as such on any machine:
>>> R
>>> ## Depends on packages:shiny, ggplot2, adegenet, ade4, reshape2, plyr
>>> library(shiny)
>>> runGitHub("blue-grama-diversity","avahoffman")
├── data
│ ├── BOGR_DATA_master.csv
│ ├── BOGR_DATA_master_metadata.docx
│ ├── BOGR_DATA_plasticity_PCA_LDA.csv
│ ├── BOGR_DATA_plasticity_master.csv
│ ├── BOGR_DATA_unsupervised_PCA_LDA.csv
│ ├── Bouteloua_genome_reference.fasta
│ ├── SITE_DATA.csv
│ └── hydroscape
These are the raw data for the analyses. BOGR_DATA_master_metadata.docx contains details about what fields in the ..master.csv data files mean and how they were calculated. ..PCA_LDA.csv files are very similar to ..master.csv but have missing data removed. Bouteloua_genome_reference.fasta is the de-novo assembled reference genome to which all SNP fragments in Bouteloua gracilis are aligned. SITE_DATA.csv contains site-level characteristics, such as climate variables. Finally, hydroscape/ contains raw and processed data for hydroscape area and includes plots of the hydroscape area (details of calculation of area can be found in Meinzer et al. 2016).
├── genomics_output
This directory contains intermediate and outputs from genomic diversity analyses, including structure plots, site heirarchy, DAPC, etc.
├── genomics_variance
This directory contains final outputs for measures of within-site genetic diversity, allowing assessment of genetic variance within site.
├── partial_climate_correlation
This directory contains correlation_vars.csv, which is used by partial_corr_matrices.R to check for partial correlations of all measures against all climate variables. Estimates and corresponding p-values for each climate variable for both phenotypic measures and phenotypic plasticity measures are produced. Correlations begin with aboveground biomass versus the climate variable; subsequent measures are added to account for remaining variance.
├── posterior_output
This directory contains posterior output, predictive checks, and plots of distributions of phenotypic measures as they are produced from src/Trait_models.R.
├── posterior_output_plasticity
This directory contains posterior output, predictive checks, and plots of distributions of phenotypic plasticity measures as they are produced from src/Plasticity_models.R.
├── resources
This directory contains several useful references for packages and theory used in this project.
├── src
│ ├── Hydroscape_area.R
│ ├── Interval_plots.R
│ ├── LDA.R
│ ├── Maps_genomics.R
│ ├── Pairwise_distance.R
│ ├── Plasticity_models.R
│ ├── Poppr_genetic_diversity.R
│ ├── Site_tree_hierarchical.R
│ ├── Total_genome_diversity.R
│ ├── Trait_models.R
│ ├── config.R
│ ├── genomics_prep
│ ├── genomics_variance.R
│ ├── local_genome_diversity.R
│ ├── partial_corr_matrices.R
│ ├── regional_genome_diversity.R
│ └── run.R
└── utils
├── color_key.csv
├── color_key_alt.csv
├── data_utils.R
├── mcmc_output.R
└── partial_corr.R
This directory contains code for preprocessing and analyzing all the data. Because genomics preprocessing is complex with multiple steps, separate bash scripts can be found in genomics_prep/. The majority of analyses and plotting can be done by executing the run.R script.