The bioinformatics chat is a podcast about computational biology, bioinformatics, and next generation sequencing.
The bioinformatics chat is produced by Roman Cheplyaka.
October 27, 2018
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.
September 24, 2018
Kaushik Panda and Keith Slotkin come on the podcast to educate us about repetitive DNA and transposable elements. We talk LINEs, SINEs, LTRs, and even Sleeping Beauty transposons! Kaushik and Keith explain why repeats matter for your whole-genome analysis and answer listeners’ questions.
August 31, 2018
Antoine Limasset joins me to talk about NGS read correction. Antoine and his colleagues built the read correction tool Bcool based on the de Bruijn graph, and it corrects reads far better than any of the current methods like Bloocoo, Musket, and Lighter.
We discuss why and when read correction is needed, how Bcool works, and why it performs better but slower than k-mer spectrum methods.