#54 Seeding methods for read alignment with Markus Schmidt

More from the bioinformatics chat All episodes →

1. 

   E59 · 21 Apr 2021 · 48 min

   #59 Proteomics calibration with Lindsay Pino

   In this episode, Lindsay Pino discusses the challenges of making quantitative measurements in the field of proteomics. Specifically, she discusses the difficulties of comparing measurements across different samples, potentially acquired in different labs, as well as a method she has developed recently for calibrating these measurements without the need for expensive reagents. The discussion then turns more broadly to questions in genomics that can potentially be addressed using proteomic measurements. Links: Talus Bioscience Matrix-Matched Calibration Curves for Asssessing Analytical Figures…

2. 

   E58 · 31 Mar 2021 · 1 hr 29 min

   #58 B cell maturation and class switching with Hamish King

   In this episode, we learn about B cell maturation and class switching from Hamish King . Hamish recently published a paper on this subject in Science Immunology, where he and his coauthors analyzed gene expression and antibody repertoire data from human tonsils. In the episode Hamish talks about some of the interesting B cell states he uncovered and shares his thoughts on questions such as «When does a B cell decide to class-switch?» and «Why is the antibody isotype correlated with its affinity?» Links: Single-cell analysis of human B cell maturation predicts how antibody class switching…

3. 

   E57 · 10 Mar 2021 · 47 min

   #57 Enhancers with Molly Gasperini

   In this episode, Jacob Schreiber interviews Molly Gasperini about enhancer elements. They begin their discussion by talking about Octant Bio, and then dive into the surprisingly difficult task of defining enhancers and determining the mechanisms that enable them to regulate gene expression. Links: Octant Bio Towards a comprehensive catalogue of validated and target-linked human enhancers (Molly Gasperini, Jacob M. Tome, and Jay Shendure)

4. 

   E56 · 17 Feb 2021 · 1 hr 30 min

   #56 Polygenic risk scores in admixed populations with Bárbara Bitarello

   Polygenic risk scores (PRS) rely on the genome-wide association studies (GWAS) to predict the phenotype based on the genotype. However, the prediction accuracy suffers when GWAS from one population are used to calculate PRS within a different population, which is a problem because the majority of the GWAS are done on cohorts of European ancestry. In this episode, Bárbara Bitarello helps us understand how PRS work and why they don’t transfer well across populations. Links: Polygenic Scores for Height in Admixed Populations (Bárbara D. Bitarello, Iain Mathieson) What is ancestry? (Iain…

5. 

   E55 · 13 Jan 2021 · 57 min

   #55 Phylogenetics and the likelihood gradient with Xiang Ji

   In this episode, we chat about phylogenetics with Xiang Ji . We start with a general introduction to the field and then go deeper into the likelihood-based methods (maximum likelihood and Bayesian inference). In particular, we talk about the different ways to calculate the likelihood gradient, including a linear-time exact gradient algorithm recently published by Xiang and his colleagues. Links: Gradients Do Grow on Trees: A Linear-Time O(N) -Dimensional Gradient for Statistical Phylogenetics (Xiang Ji, Zhenyu Zhang, Andrew Holbrook, Akihiko Nishimura, Guy Baele, Andrew Rambaut, Philippe…

6. 

   E53 · 18 Nov 2020 · 1 hr 3 min

   #53 Real-time quantitative proteomics with Devin Schweppe

   In this episode, Jacob Schreiber interviews Devin Schweppe about the analysis of mass spectrometry data in the field of proteomics. They begin by delving into the different types of mass spectrometry methods, including MS1, MS2, and, MS3, and the reasons for using each. They then discuss a recent paper from Devin, Full-Featured, Real-Time Database Searching Platform Enables Fast and Accurate Multiplexed Quantitative Proteomics that involved building a real-time system for quantifying proteomic samples from MS3, and the types of analyses that this system allows one to do. Links:…

7. 

   E52 · 27 Oct 2020 · 43 min

   #52 How 23andMe finds identical-by-descent segments with William Freyman

   In this episode, Will Freyman talks about identity-by-descent (IBD): how it’s used at 23andMe , and how the templated positional Burrows-Wheeler transform can find IBD segments in the presence of genotyping and phasing errors. Links: Fast and robust identity-by-descent inference with the templated positional Burrows-Wheeler transform (William A. Freyman, Kimberly F. McManus, Suyash S. Shringarpure, Ethan M. Jewett, Katarzyna Bryc, the 23andMe Research Team, Adam Auton) 23andMe research

8. 

   E51 · 7 Oct 2020 · 1 hr 14 min

   #51 Basset and Basenji with David Kelley

   In this episode, Jacob Schreiber interviews David Kelley about machine learning models that can yield insight into the consequences of mutations on the genome. They begin their discussion by talking about Calico Labs, and then delve into a series of papers that David has written about using models, named Basset and Basenji, that connect genome sequence to functional activity and so can be used to quantify the effect of any mutation. Links: Calico Labs Basset: Learning the regulatory code of the accessible genome with deep convolutional neural networks (David R. Kelley, Jasper Snoek, and John…

9. 

   E50 · 10 Sep 2020 · 56 min

   #50 ENCODE3 with Jill Moore

   In this episode, Jacob Schreiber interviews Jill Moore about recent research from the ENCODE Project . They begin their discussion with an overview and goals of the ENCODE Project, and then discuss a bundle of papers that were recently published in various Nature journals and the flagship paper, Expanded encyclopaedias of DNA elements in the human and mouse genomes . They conclude their discussion by talking about the challenges with managing a large project as a trainee in a consortium setting. Links: Expanded encyclopaedias of DNA elements in the human and mouse genomes (The ENCODE Project…

10. 

    E49 · 19 Aug 2020 · 1 hr 4 min

    #49 Most Permissive Boolean Networks with Loïc Paulevé

    In systems biology, Boolean networks are a way to model interactions such as gene regulation or cell signaling. The standard interpretations of Boolean networks are the synchronous, asynchronous, and fully asynchronous semantics. In this episode, Loïc Paulevé explains how the same Boolean networks can be interpreted in a new, “most permissive” way. Loïc proved mathematically that his semantics can reproduce all behaviors achievable by a compatible quantitative model, whereas the traditional interpretations in general cannot. Furthermore, it turns out that deciding whether a certain state in…