Data and code for 'Pseudogenes act as a neutral reference for detecting selection in prokaryotic pangenomes'
Notice bibliographique
Résumé
This repository contains the code and files for reproducing the analyses and results reported in 'Pseudogenes act as a neutral reference for detecting selection in prokaryotic pangenomes' by Gavin M. Douglas and B. Jesse Shapiro (https://doi.org/10.1038/s41559-023-02268-6). File organization and descriptions: code/ - Contains GitHub repository releases of code used in manuscript (the other folders contain datafiles only). This code is provided here as well as on GitHub to ensure long-term access. handy_pop_gen-1.1.0/ - release v1.1.0 of the convenience repository (used for specific data processing and analysis steps referred to in the manuscript). pangenome_pseudogene_null-1.1.0/ - Main code repository for manuscript. broad_pangenome_analysis/ element_info/element_counts.tsv.gz - Counts of (filtered) pseudogenes and intact genes called per genome accession. element_info/gene_sizes.tsv.gz - Gene sizes in base-pairs. element_info/pseudogene_sizes.tsv.gz - Filtered pseudogene sizes in base-pairs. element_info/element_percent_coverage/*tsv.gz - Tables containing the percent genome coverage of genes and pseudogenes, by accession and averaged over accessions per species separately. example_Mycoplasmopsis_bovis_panaroo_output.csv.gz - Panaroo output table for Mycoplasmopsis bovis, which was used for an example. Corresponds to the gene_presence_absence.csv file in the raw Panaroo output. focal_and_non.focal_full_to_short.tsv.gz - Mapfile of full to short (and unique) species ids used in analysis. Primarily to include species ids in cluster names without making them unnecessarily long. genome_info/accessions.tsv.gz - Genome accessions used for broad pangenome analysis (note that not all genome accessions could be downloaded [and were ignored], which is indicated in the "could_download" column). genome_info/genome_sizes.tsv.gz - Sizes of all genomes used for the broad pangenome analysis. metrics_additional_subsamples.tsv.gz - Contains columns also found in the pangenome_and_related_metrics.tsv.gz file below, but based on genome subsamplings of 3 and 20, rather than 9. model_output/pangenome_linear_models.rds - R Data Serialization files containing the output of R linear model objects (generated by lm and provided as an R list object). There are separate elements in the list for the mean number of genes, genomic fluidity, percentage singletons (si), and si/sp. model_output/linear_model_coef.tsv.gz - Coefficient summary table for all linear models. pangenome_and_related_metrics.tsv.gz - Metrics used for broad pangenome analysis across 670 prokaryotic species. Note that this table was filtered down to 668 species after excluding those with < 9 genomes. pangenome_and_related_metrics_filt.tsv.gz - Filtered table, as described above. taxonomy.tsv.gz - Taxonomy for all species used for this analysis, taken from GTDB. Row names are species names. indepth_10_species_analysis/ cluster_breakdown_tables/ - Folder containing tables providing breakdown of how clusters are distributed by element type, pangenome partition, and species. Provided for easy plotting. cluster_COG_annot.tsv.gz - Mapping of cluster IDs to COG annotations. cluster_filt_lengths_and_additional.tsv.gz - Metadata on clusters, most pertinently the length of the representative sequence in the cluster (which was used to filter out some clusters, below the cut-off which pseudogenes could not be called). cluster_member_breakdown.tsv.gz - Table providing information on each element (called pseudogenes and intact genes) and provides information such as what cluster they are part of, what species and genome accession they are found in, etc. cluster_types.rds - R Data Serialization file containing R list providing breakdown of all clusters into categories (intact/pseudogene/mixed, where mixed means containing both pseudogene and intact elements). COG_enrichment_results/ultra.cloud-COG-gene-enrichments.tsv.gz - Output file with enrichment test summaries for COG IDs in significant COG categories, which was run for the ultra-cloud pangenome partition model only. element_glmm_input.tsv.gz - Table containing all information used for fitting generalized linear mixed models. focal_species.txt - Names of species used for the in-depth analysis. genome_info/ - Folder containing the genome accessions (and the corresponding genome sizes) for all ten analyzed species. glmm_output/ - Folder containing R Data Serialization files containing output R objects after fitting generalized linear mixed models (only ultra-rare files are present, due to file size constraints). per_genome_element.type_percent_coverages.rds - R Data Serialization file containing R list providing the percent coverage by intact genes vs pseudogenes per accession (nested by species)
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,003 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,006 | 0,009 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,005 | 0,004 |
| Science ouverte | 0,005 | 0,005 |
| Intégrité de la recherche | 0,003 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,461 | 0,405 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».