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25_rank_data.yml
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25_rank_data.yml
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target_default: 25_rank_data
include:
- 24_check_data.yml
packages:
- dplyr
- ggplot2
- cowplot
sources:
- 25_rank_data/src/site_dat_rankings.R
- 25_rank_data/src/ranking_fig_fxns.R
- 25_rank_data/src/chemical_rankings.R
targets:
25_rank_data:
depends:
- top_parents
all_samples:
command: get_all_samples(chem_data)
# Most impacted SITE (RANKINGS) (all sites)
# nchems: rankings based on mean # chems detected per sample, max # chems/sample, n unique chems detected
# conc: rankings based on mean and max conc of summed detected chems
# bench: rankings based on mean and max benchmark ratio
# EAR: rankings based summed max EAR by site
rank_site_n_chems:
command: get_nchems_sites(chemicalSummary_conc, all_samples)
rank_site_conc:
command: get_conc_sites(chemicalSummary_conc, all_samples)
rank_site_EAR:
command: get_ear_sites(chemicalSummary_deg_meto, all_samples)
rank_site_bench:
command: get_bench_sites(chemicalSummary_bench_deg_meto, all_samples)
rank_site_mix:
command: get_mix_sites(site_mix_metrics_all)
site_rankings:
command: bind_rows(rank_site_n_chems, rank_site_bench, rank_site_mix)
site_rankings_final:
command: add_final_rank(site_rankings, sites)
figures/ms_supplement_figures/site_rankings_table.csv:
command: create_site_rank_table(site_rankings_final, sites, out_file = target_name)
figure/site_rankings.png:
command: make_site_fig(target_name, site_rankings, sites)
figures/ms_figures/site_rankings_tile.png:
command: make_site_tile(target_name, site_rankings, sites)
site_avg_rankings:
command: calc_avg_rankings(site_rankings, sites)
figure/site_avg_rankings_disturbance.png:
command: plot_avg_rankings(target_name, site_avg_rankings, site_info)
# Top CHEMICALS of concern (RANKINGS) (maybe top 5-10 from each stat?)
# ndetect: detection frequency (site and sample)
# conc: rankings based on mean and max conc of chem
# bench: rankings based on mean and max benchmark ratio of chem
# EAR: rankings based on mean of max EAR by chem
figures/ms_supplement_figures/chem_metadata.csv:
command: summarize_chem_meta(file_name = target_name, chem_vals = all_chems,
chem_crosswalk, chem_info_all, chems_missing_toxcast, chems_missing_bench)
figure/chem_summary.csv:
command: summarize_chems(file_name = target_name, chem_vals = all_chems,
chem_crosswalk, chem_info_all, chemicalSummary_conc)
#figure/site_summary.csv:
# command: summarize_chems_by_site(file_name = target_name, chem_conc, chem_ear, chem_bench)
#top_chems_ear:
# command: calc_chem_tox_hits(chemicalSummary, chemicalSummary_conc, sites_detect = I(8), sites_hit = I(4))
parent_chem_rank_metrics:
command: calc_parent_tox_hits(parent_sums, mixtures = chem_mix_metrics_all)
top_parents:
command: filter_parents(parent_chem_rank_metrics, f_detect_prob = I(.2), f_detect_sites_prob = I(.5),
f_detect_months = I(12), f_hit_prob = I(.1), f_hit_sites_prob = I(0.25))
figures/ms_supplement_figures/top_parent_compounds.csv:
command: write.csv(top_parents, target_name, row.names = FALSE)
#top_chems_ear_deg_meto:
# command: calc_chem_tox_hits(chemicalSummary_deg_meto, chemicalSummary_conc, I(8), I(4))
#top_chems_ear_deg_acet:
# command: calc_chem_tox_hits(chemicalSummary_deg_acet, chemicalSummary_conc)
# TIMING of highest impact (RANKINGS) by month
# nchems: mean # chemicals across sites, unique chemicals relative to all other periods
# conc: mean, max, and min concentration across sites
# benchmark: mean, max and min concentrations across sites
# EAR: mean, min, max of max EAR by site