MétaCan
Menu
Retour à la cohorte
Enregistrement W4394104236 · doi:10.6084/m9.figshare.20486767

Additional file 2 of Mendelian randomization of circulating proteome identifies actionable targets in heart failure

2022· dataset· en· W4394104236 sur OpenAlexaff
Louis-Hippolyte Minvielle Moncla, Samuel Mathieu, Mame Sokhna Sylla, Yohan Bossé, Sébastien Thériault, Benoît J. Arsenault, Patrick Mathieu

Notice bibliographique

RevueOpen MIND · 2022
Typedataset
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueMachine Learning in Bioinformatics
Établissements canadiensUniversité LavalInstitut universitaire de cardiologie et de pneumologie de Québec
Organismes subventionnairesnon disponible
Mots-clésMendelian randomizationHeart failureComputational biologyProteomeBioinformaticsComputer scienceBiologyGeneticsMedicineInternal medicineGeneGenetic variants

Résumé

récupéré en direct d'OpenAlex

Additional file 2: Suppl. Table 1. Mendelian randomization INTERVAL (P < 1E-03). Results of MR analysis for the nineteen causal candidate proteins in INTERVAL. Table includes: the aptamer and corresponding id code along with the protein name; the number of SNPs used as IVs in MR for each protein; the median, minimum and maximum F-statistics value for IVs; the beta, standard error and p-values for Inverse Variance Weighted and Weighted Median methods; heterogeneity tests (Cochrane’s Q test and intercept Egger test). Suppl. Table 2. Mendelian randomization INTERVAL (P < 1E-03) (all results). Results of MR analysis for all the proteins with enough IVs in INTERVAL. Table includes: the aptamer and corresponding id code along with the protein name; the number of SNPs used as IVs in MR for each protein; the median, minimum and maximum F-statistics value for IVs; the beta, standard error and p-values for Inverse Variance Weighted and Weighted Median methods; heterogeneity tests (Cochrane’s Q test and intercept Egger test). Suppl. Table 3. Mendelian randomization INTERVAL (P < 1E-05). Results of MR analysis for the nineteen causal candidate proteins in INTERVAL. Table includes: the aptamer and corresponding id code along with the protein name; the number of SNPs used as IVs in MR for each protein; the median, minimum and maximum F-statistics value for IVs; the beta, standard error and p-values for Inverse Variance Weighted and Weighted Median methods; heterogeneity tests (Cochrane’s Q test and intercept Egger test). Suppl. Table 4. Mendelian randomization INTERVAL (Wald ratio; P < 1E-05). Results of mendelian randomization with Wald ratio, using INTERVAL as the exposure. Wald ratio was calculated using the most significant SNP for proteins not presenting enough instruments for previously described two-sample mendelian randomization. Table includes: the aptamer and corresponding id code along with the protein name; the corresponding lead SNP identification; the beta, standard error and p-values for the GWAS outcome, the GWAS pQTL and for the Wald ratio. Suppl. Table 5. Reverse Mendelian Randomization for the nineteen causal candidates. Results of reverse MR for the nineteen causal candidate proteins identified in the study. Table includes: the aptamer and corresponding id code along with the protein name; the number of SNPs used as IVs in MR for each protein; the beta, standard error and p-values for Inverse Variance Weighted and Weighted Median methods; heterogeneity tests (Cochrane’s Q test and intercept Egger test). Suppl. Table 6. Mendelian randomization deCODE (P < 1E-03). Results of mendelian randomization for all nineteen causal candidate proteins, using deCODE [21] as the exposure. Table includes: the aptamer and corresponding id code along with the protein name; the number of SNPs used as IVs in MR for each protein; the median, minimum and maximum F-statistics value for IVs; the beta, standard error and p-values for Inverse Variance Weighted and Weighted Median methods; heterogeneity tests (Cochrane’s Q test and intercept Egger test). Suppl. Table 7. Mendelian randomization deCODE (P < 1E-05). Results of mendelian randomization for all nineteen causal candidate proteins, using deCODE [21] as the exposure. Table includes: the aptamer and corresponding id code along with the protein name; the number of SNPs used as IVs in MR for each protein; the median, minimum and maximum F-statistics value for IVs; the beta, standard error and p-values for Inverse Variance Weighted and Weighted Median methods; heterogeneity tests (Cochrane’s Q test and intercept Egger test). Suppl. Table 8. Mendelian randomization deCODE (Wald ratio; P < 1E-05). Results of mendelian randomization with Wald ratio, using deCODE [21] as the exposure. Wald ratio was calculated using the most significant SNP for protein not presenting enough instruments for previously described two-sample mendelian randomization. Table includes: the aptamer and corresponding id code along with the protein name; the corresponding lead SNP identification; the beta, standard error and p-values for the GWAS outcome, the GWAS pQTL and for the Wald ratio. Suppl. Table 9. Ligand-receptor pairs generated from causal blood candidate proteins. Ligand-receptor interactions for causal candidate blood proteins by using the comprehensive repository reported by Shao et al. [24]. Bold are causal candidate blood proteins. Suppl. Table 10. Gene Ontology (molecular function) for ligand-receptor pairs generated from the causal candidate proteins. Enrichment of all ligand-receptor pairs in Gene Ontology (GO Molecular Function). Suppl. Table 11. Network nodes (proteins) and degree. Degree for each protein in the network. Suppl. Table 12. Pathway enrichment (KEGG) for the network. Summary results of enrichment for all proteins in the network by using the Kyoto Encyclopedia of Gene and Genomes (KEGG) database. Suppl. Table 13. Cross-phenotype association analysis of HF by using iCPAG. Summary of iCPAG results. Trait 1 is the GWAS data from the HERMES study; Trait2 is the trait-disorder, which is compared to trait1 for sharing a similar genetic architecture. Reported in the table: p-value, FDR and Bonferroni adjusted p-value for the Fisher’s exact test; the Chao-Sorensen similarity index between trait 1 and trait 2; the list of SNPs in common between trait 1 and 2; links to corresponding experimental factor ontology (EFO) in EMBL-EBI database. Suppl. Table 14. Multi-trait MR. Table summarizing the 31 traits and diseases used in the multi-trait MR. Suppl. Table 15. Results of multivariable MR corrected for cardiovascular traits. Summary of multivariable MR and univariate MR for BAG3, MIF and APOA5. Univariate exposure is HF, whereas multivariate exposure is HF corrected for the selected trait in parenthesis. Reported are: estimate (beta), se (standard error) and p-value. DBP: diastolic blood pressure; SBP: systolic blood pressure; CAD: coronary artery disease. Suppl. Table 16. Therapeutic Target Database (TTD) for the causal candidate proteins. Summary results of druggable genome in the Therapeutic Target Database (TTD) for the causal candidate proteins. Reported are: the gene symbol and name; target type; disease for which there is an indication; drugs associated to the target. NA: not available. Suppl. Table 17. Drug Gene interaction Database (DGIdb) for the causal candidate proteins. Summary of druggable genome in the Drug Interaction database (DGIdb) for the causal candidate proteins. Reported are: the gene symbol; drug associated with the target; sources and pmids from the National Library of Medicine. Suppl. Table 18. Open Targets for the causal candidate proteins. Summary of druggable genome in the Open Targets for the causal candidate proteins. Reported are: gene symbol; drugs associated with the target; drug type (sm: small molecule, ab: antibody); category ab is the prediction confidence that the target is tractable for the development of an antibody.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Jeu de données · Signal consensuel: Jeu de données
Score de désaccord entre enseignants0,906
Score d'incertitude au seuil0,578

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,9060,000

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.

Tête enseignante Opus0,010
Tête enseignante GPT0,270
Écart entre enseignants0,260 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreJeu de données

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueOpen MINDMême sujetMachine Learning in BioinformaticsTravaux en français237 207