GitHub - dachbrown/code-bioinformatics-machine-learning: Initial code upload from "Investigating Multidrug Resistance in Escherichia coli with Phylogenetics and Machine Learning"

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Initial code upload from "Investigating Multidrug Resistance in Escherichia coli with Phylogenetics and Machine Learning"

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Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
.gitattributes		.gitattributes
00_viz_compare_pangenome_and_resampling.py		00_viz_compare_pangenome_and_resampling.py
03_run_ml_rfc_experiment.py		03_run_ml_rfc_experiment.py
045_find_hypos.py		045_find_hypos.py
20221216_snp_sites_consensus_test.consensus		20221216_snp_sites_consensus_test.consensus
20221216_snp_sites_consensus_test.vcf		20221216_snp_sites_consensus_test.vcf
4B_help_roary_plots.py		4B_help_roary_plots.py
4_prepare_data_matrices.py		4_prepare_data_matrices.py
README_setup_R_in_VS_Code.md		README_setup_R_in_VS_Code.md
README_snp_sites.txt		README_snp_sites.txt
README_test_prokka_roary.txt		README_test_prokka_roary.txt
fp_ws_shell_10_test_roc_auc_SMOTE_macro_auroc_0.864.png		fp_ws_shell_10_test_roc_auc_SMOTE_macro_auroc_0.864.png
hpc_galick_gun_environment_from_history.yml		hpc_galick_gun_environment_from_history.yml
hpc_model_hypers_per_rfc_and_sel_feat.py		hpc_model_hypers_per_rfc_and_sel_feat.py
hpc_viz_importances.py		hpc_viz_importances.py
ml_final_random_forest_functions_20221014.py		ml_final_random_forest_functions_20221014.py
modified_ftr_to_gb_rf_ftp.py		modified_ftr_to_gb_rf_ftp.py
ns_prot_mutS.fasta		ns_prot_mutS.fasta
ns_prot_mutS.vcf		ns_prot_mutS.vcf
process_search_hypotheticals_MOD.py		process_search_hypotheticals_MOD.py
run_correlation_analysis_pagel.R		run_correlation_analysis_pagel.R
run_make_consensus.py		run_make_consensus.py
run_snpsites.py		run_snpsites.py
split_data_to_matrices.py		split_data_to_matrices.py
subset_900_ns_protein_mutS.faa		subset_900_ns_protein_mutS.faa
wip_run_d_statistic.R		wip_run_d_statistic.R
wip_run_phylogenetic_pca.R		wip_run_phylogenetic_pca.R
wip_run_spearmans_rank_corr.R		wip_run_spearmans_rank_corr.R