Analysis scripts for Lipshutz, Hibbins, et al. 2023. A brief description of the purpose of each script is outlined here. Scripts were run in Python v3 and R v4.
CN_behavior_analyses.R - Examines and visuzalizes attack rate and distance from mount by nest strategy and sex, from simulated territorial intrusions.
CN_testosterone_analyses.R - Examines and visuzalizes plasma testosterone levels by nest strategy and sex, from enzyme immunoassay.
Cavity.Agg.Collect.Allyears.csv - Input file for behavior and testosterone analyses
DEGs_vs_Divergence.R - Visualizes and correlates number of differentially expressed genes between species pairs by degree of evolutionary divergence, for each of five families
Divergence_DEGs.csv - Input file for DEGs vs. Divergence
bentz_gene_permutation_aggmodels.R - Tests for significant overlap between our PhyloDEGs associated with nesting strategy and a list of bird behavioral candidate genes generated by Bentz et al. 2021.
gene_permutation_notbirds_aggmodel.R - Tests for significant overlap between our PhyloDEGs associated with nesting strategy and lists of behavioral candidate genes from several non-bird studies.
aggression_phyloglm.R - Fits phylogenetic generalized linear mixed models (PGLMs) for the relationship of attack rate with nesting strategy, testosterone, and physical distance.
bird_wgcna_pglm.R - Fits PGLMs with three nesting strategies to WGCNA modules inferred with data from both sexes.
bird_wgcna_pglm_F.R - Fits PGLMs with three nesting strategies to WGCNA modules inferred for females.
bird_wgcna_pglm_M.R - Fits PGLMs with three nesting strategies to WGCNA modules inferred for males.
wgcna_2level_pglm.R - Fits PGLMs with two nesting strategies to WGCNA modules inferred with data from both sexes.
wgcna_pglm_2levels_F.R - Fits PGLMs with two nesting strategies to WGCNA modules inferred for females.
wgcna_pglm_2levels_M.R - Fits PGLMs with two nesting strategies to WGCNA modules inferred for males.
bird_expression_2levels_model_fdr_correction.py - Applies false discovery rate correction to expression PGLMs with two nesting strategies.
bird_expression_agg_model_fdr_correction.py - Applies false discovery rate correction to expression PGLMs with three nesting strategies.
bird_expression_analyis_2levels.R - Fits a PGLM with two nesting strategies to log-expression of an individual gene.
bird_expression_analysis_attrate.R - Fits a PGLM with three nesting strategies to log-expression of an individual gene.
get_convergent_agg_genes.R - Gets putatively convergent genes significantly associated with aggression in three-strategy models.
get_convergent_nestingstrat_2level_genes.R - Gets putatively convergent genes significantly associated with nesting strategy in two-strategy models.
get_convergent_nestingstrat_genes.R - Gets putatively convergent genes significantly associated with nesting strategy in three-strategy models.
job_scripts/ - SLURM scripts for running gene expression PGLM analyses on high-performance computing clusters.
summarize_bird_expression_2level_results.py - Counts genes associated with each model term in two-strategy PGLMs, including the sign of the inferred coefficient.
summarize_bird_expression_agg_results.py - Counts genes associated with each model term in three-strategy PGLMs, including the sign of the inferred coefficient.
CavNesting_RankDivergence.Rmd - Conducts RRHO analysis for both sexes combined.
CavNesting_RankDivergence_Females.Rmd - Conducts RRHO analysis for female expression.
CavNesting_RankDivergence_Males.Rmd - Conducts RRHO analysis for male expression.
count_RRHO_shared.R - Counts highly concordantly expressed genes shared across multiple RRHO family comparisons.
CN_raw_counts.csv - Expression data input file for WGCNA, for both sexes
CN_WGCNA_traits.csv - Trait data input file for WGCNA, for both sexes
WGCNA_cavity_Nesting_allind_cytoscape.R - Runs weighted gene co-expression network analysis for gene expression using data from both sexes. Includes output for cytoscape network visualization.
WGCNA_cavity_Nesting_male.R - Runs weighted gene co-expression network analysis for gene expression using data from males only.
WGCNA_cavity_nesting_female.R - Runs weighted gene co-expression network analysis for gene expression using data from females only.
WGCNA_downstream_analyses.R - Visualizes WGCNA by nest strategy, aggression, and sex. For samples with behavioral assays followed by immediate collection, includes latency analysis.
WGCNA_latency.csv - Input file for WGCNA latency analysis, including module eigengenes.