#26 Feature selection, Relief and STIR with Trang Lê - a podcast by Roman Cheplyaka

Relief is a statistical method to perform feature selection. It could be used,
for instance, to find genomic loci that correlate with a trait or genes whose
expression correlate with a condition. Relief can also be made sensitive to
interaction effects (known in genetics as epistasis).

In this episode, Trang Lê joins me
to talk about Relief and her version of Relief called STIR (STatistical
Inference Relief). While traditional Relief algorithms could only rank
features and needed a user-supplied threshold to decide which features to
select, Trang’s reformulation of Relief allowed her to compute p-values
and make the selection process less arbitrary.

Links:

• Paper: STatistical Inference Relief (STIR) feature selection


• STIR on GitHub


• Relief on Wikipedia


• The original Relief paper by Kira and Rendell (1992)


• Epistasis: what it means, what it doesn’t mean, and statistical methods to detect it in humans

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