Use case: A data scientist collating data
General description: Someone who wants to maximise the amount of relevant data they can obtain with minimal effort. I.e. able to search for raw or processed (normalised) transcriptomic data generated from the same platform/pipeline/analytical approach applied to samples from a specific tissue from animals/individuals that have genotype/phenotype x. Data likely to be from different labs that have used different ontologies and/or different resolutions of the same annotation framework.
Typical issues: which onotology terms to use e.g. search for brain or temporal cortex? [may want to bucket all together (so temporal cortex == brain) or not], genotype/phenotype mapping; can these be captured by text rather than ids? A fuzzy search to handle the different resolutions? Comparison of experimental factors analysed, how was the data generated and processed?
Use case: A data scientist collating data General description: Someone who wants to maximise the amount of relevant data they can obtain with minimal effort. I.e. able to search for raw or processed (normalised) transcriptomic data generated from the same platform/pipeline/analytical approach applied to samples from a specific tissue from animals/individuals that have genotype/phenotype x. Data likely to be from different labs that have used different ontologies and/or different resolutions of the same annotation framework. Typical issues: which onotology terms to use e.g. search for brain or temporal cortex? [may want to bucket all together (so temporal cortex == brain) or not], genotype/phenotype mapping; can these be captured by text rather than ids? A fuzzy search to handle the different resolutions? Comparison of experimental factors analysed, how was the data generated and processed?
Owner: Emma Laing (LILLY)