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Spotlight Presentation: Foundational model building with single-cell RNA-Seq data

26 Sep 2024
Sierra B
Data Quality , Target Identification , Lead Generation & Optimization , Drug Response Prediction
Spotlight Presentation: Foundational model building with single-cell RNA-Seq data

 

 

 

 

Strand will present progress on the following subproblems in the use of single-cell RNA-Seq data for drug discovery:

  • An AWS data lake capable of ingesting and processing single-cell RNA-Seq data with associated metadata at scale

           N/A

  • Semi-automated LLM-based ingestion to a schema with ≈35 fields of single-cell RNA-Seq + metadata of 3 disease datasets -- UC, AD and FTD -- from GEO.  We show an improvement in turnaround time of ≈3x-5x

  • A standardized single-cell pipeline that generates normalized counts from fastqs for ingested data

  • Embeddings of the single-cell data for pretraining on an LLM [see for e.g scBERT]. We show how such embeddings might be used to remove batch effect and hence integrate data.

Industry Expert
Radhakrishna Bettadapura, Vice President, Business Development - Strand Life Sciences