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Elucidata: Utilizing Public Transcriptomics Databases for Meta-Analysis
The biomedical data landscape is fragmented, with several isolated and heterogeneous data sources that use varying formats, syntaxes, schemas, and entity notations. This leaves biomedical researchers with severe logistical and technical challenges to find, query, and integrate data into relevant cohorts.

Our solution to this problem is the Polly Public OmixAtlas, housing transcriptomics datasets ready to be queried & analyzed. This data becomes analysis-ready in two main steps: First is Data engineering, where data formats become consistent. The second is metadata harmonization, which uses NLP models to ensure that all the metadata fields follow the same vocabulary.

With the proper scientific context, meta-analysis and integration of multiple datasets are now possible and help uncover significant insights in the form of differentially expressed biomarkers and pathways. Tune in on 1st Dec, 11:00 AM (EST), as our experts demonstrate how to effectively utilize public transcriptomics databases, like GEO for large-scale meta-analysis.

Some topics we'll cover in the presentation:
- The challenges associated with using public data for meta-analysis

- An improved workflow for building interesting cohorts for subsequent integrative analysis

- Case studies to showcase how one can perform meta-analysis on Polly to identify potential gene biomarkers, enriched pathways, and new hypotheses about pathogenic mechanisms.

Mya Steadman - Bioinformatics Scientist
Yogesh Lakhotia - Product Manager
Nobal Dhruw - Solutions Manager


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