Management of Molecular Data in DINA with SeqDB
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Notice bibliographique
Résumé
Agriculture and Agri-Food Canada (AAFC) is home to numerous specimen and environmental collections generating highly relational data sets that are analyzed using molecular methods (Sanger and NGS). The need to have a system to properly manage these data sets and to capture accurate, standardized metadata over entire laboratory workflows has been a long-term strategic vision of the Biodiversity group at AAFC. Without robust tracking, many difficulties arise when trying to publish or submit data to external repositories. To even know what work has been carried out on individual collection records over a researchers career becomes a demanding task if the information is retrievable at all. SeqDB was built to resolve these issues by centralizing, standardizing and improving the availability and data quality of source specimen collection data that is being studied using molecular methods. SeqDB also facilitates integration with tools and external repositories in order to take the burden off researchers and technicians having to create adequate systems to track and mobilize their data sets, allowing them to focus on research and collection management. The development of SeqDB aligns with agile development methodologies and attempts to fulfill rapidly emerging needs from genetics and genomics research, which can evolve and fade quickly at times or be without clear requirements. The success of SeqDB as an application supporting DNA sequencing workflows has put it in the same space as other monolithic architectures before it. As the feature set to support the application continues to increase, the number of software developers vs operations and maintenance staff is difficult to rebalance in our organisation. In an effort to manage the scope for the project and ensure we are able to continue to deliver on our mandate, the sequence tracking workflows of the application will become part of the DINA ecosystem (“ DI gital information system for NA tural history data”, https://dina-project.net). Other functions of SeqDB such as collections management and taxonomy tree curation, will be replaced with the DINA modules implementing these functions. In order to allow SeqDB to become a module of DINA, it has been decided to refactor the application to base it on a Service Oriented Architecture. By doing so, all molecular data of SeqDB will be exposed as JSON API Web Services (JavaScript object notation application programming interface) allowing other modules, user interfaces and the current SeqDB application to communicate in a standardised way. The new architecture will also bring an important technology upgrade for SeqDB where the front end will eventually become a project in itself.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
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 découle