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#34 Power laws and T-cell receptors with Kristina Grigaityte

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Contenido proporcionado por Roman Cheplyaka. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Roman Cheplyaka o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

An αβ T-cell receptor is composed of two highly variable protein chains, the α chain and the β chain. However, based only on bulk DNA or RNA sequencing it is impossible to determine which of the α chain and β chain sequences were paired in the same receptor.

In this episode, Kristina Grigaityte talks about her analysis of 200,000 paired αβ sequences, which have been obtained by targeted single-cell RNA sequencing. Kristina used the power law distribution to model the T-cell clone sizes, which led her to reject the commonly held assumptions about the independence of the α and β chains. We also talk about Bayesian inference of power law distributions and about mixtures of power laws.

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If you enjoyed this episode, please consider supporting the podcast on Patreon.

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70 episodios

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Manage episode 237107179 series 1537951
Contenido proporcionado por Roman Cheplyaka. Todo el contenido del podcast, incluidos episodios, gráficos y descripciones de podcast, lo carga y proporciona directamente Roman Cheplyaka o su socio de plataforma de podcast. Si cree que alguien está utilizando su trabajo protegido por derechos de autor sin su permiso, puede seguir el proceso descrito aquí https://es.player.fm/legal.

An αβ T-cell receptor is composed of two highly variable protein chains, the α chain and the β chain. However, based only on bulk DNA or RNA sequencing it is impossible to determine which of the α chain and β chain sequences were paired in the same receptor.

In this episode, Kristina Grigaityte talks about her analysis of 200,000 paired αβ sequences, which have been obtained by targeted single-cell RNA sequencing. Kristina used the power law distribution to model the T-cell clone sizes, which led her to reject the commonly held assumptions about the independence of the α and β chains. We also talk about Bayesian inference of power law distributions and about mixtures of power laws.

Links:

If you enjoyed this episode, please consider supporting the podcast on Patreon.

  continue reading

70 episodios

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