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#70 Prioritizing drug target genes with Marie Sadler

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Manage episode 390813219 series 1537951
Content provided by Roman Cheplyaka. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Roman Cheplyaka or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, Marie Sadler talks about her recent Cell Genomics paper, Multi-layered genetic approaches to identify approved drug targets.

Previous studies have found that the drugs that target a gene linked to the disease are more likely to be approved. Yet there are many ways to define what it means for a gene to be linked to the disease. Perhaps the most straightforward approach is to rely on the genome-wide association studies (GWAS) data, but that data can also be integrated with quantitative trait loci (eQTL or pQTL) information to establish less obvious links between genetic variants (which often lie outside of genes) and genes. Finally, there’s exome sequencing, which, unlike GWAS, captures rare genetic variants. So in this paper, Marie and her colleagues set out to benchmark these different methods against one another.

Listen to the episode to find out how these methods work, which ones work better, and how network propagation can improve the prediction accuracy.

Links:

Thank you to Jake Yeung, Michael Weinstein, and other Patreon members for supporting this episode.

  continue reading

70 episodes

Artwork
iconShare
 
Manage episode 390813219 series 1537951
Content provided by Roman Cheplyaka. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Roman Cheplyaka or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, Marie Sadler talks about her recent Cell Genomics paper, Multi-layered genetic approaches to identify approved drug targets.

Previous studies have found that the drugs that target a gene linked to the disease are more likely to be approved. Yet there are many ways to define what it means for a gene to be linked to the disease. Perhaps the most straightforward approach is to rely on the genome-wide association studies (GWAS) data, but that data can also be integrated with quantitative trait loci (eQTL or pQTL) information to establish less obvious links between genetic variants (which often lie outside of genes) and genes. Finally, there’s exome sequencing, which, unlike GWAS, captures rare genetic variants. So in this paper, Marie and her colleagues set out to benchmark these different methods against one another.

Listen to the episode to find out how these methods work, which ones work better, and how network propagation can improve the prediction accuracy.

Links:

Thank you to Jake Yeung, Michael Weinstein, and other Patreon members for supporting this episode.

  continue reading

70 episodes

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