the bioinformatics chat
Roman Cheplyaka
the bioinformatics chat
Roman Cheplyaka
Wednesday 17 February 2021 : Polygenic risk scores (PRS) rely on the genome-wide association studies (GWAS) to predict the phenotype based on the genotype. However, the...
Wednesday 13 January 2021 : 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...
Wednesday 16 December 2020 : In this episode, Markus Schmidt explains how seeding in read alignment works. We define and compare k-mers, minimizers, MEMs, SMEMs, and...
Wednesday 18 November 2020 : In this episode, Jacob Schreiber interviews Devin Schweppe about the analysis of mass spectrometry data in the field of proteomics. They...
Tuesday 27 October 2020 : In this episode, Will Freyman talks about identity-by-descent (IBD): how it’s used at 23andMe, and how the templated positional...
Wednesday 07 October 2020 : In this episode, Jacob Schreiber interviews David Kelley about machine learning models that can yield insight into the consequences...
Thursday 10 September 2020 : In this episode, Jacob Schreiber interviews Jill Moore about recent research from the ENCODE Project. They begin their discussion with an...
Wednesday 19 August 2020 : In systems biology, Boolean networks are a way to model interactions such as gene regulation or cell signaling. The standard interpretations...
Wednesday 29 July 2020 : In this episode, Jacob Schreiber interviews Marinka Zitnik about applications of machine learning to drug development. They begin their...
Wednesday 24 June 2020 : NGLess is a programming language specifically targeted at next generation sequencing (NGS) data processing. In this episode we chat with its...
Wednesday 27 May 2020 : In this episode, I continue to talk (but mostly listen) to Sergey Koren and Sergey Nurk. If you missed the previous episode, you should...
Wednesday 20 May 2020 : In this episode, Sergey Nurk and Sergey Koren from the NIH share their thoughts on genome assembly. The two Sergeys tell the stories behind...
Wednesday 29 April 2020 : Porcupine is a molecular tagging system—a way to tag physical objects with pieces of DNA called molecular bits, or molbits for...
Friday 27 March 2020 : Will Townes proposes a new, simpler way to analyze scRNA-seq data with unique molecular identifiers (UMIs). Observing that such data is not...
Friday 28 February 2020 : In this episode, we hear from Amatur Rahman and Karel Břinda, who independently of one another released preprints on the same concept,...
Monday 27 January 2020 : Kris Parag is here to teach us about the mathematical modeling of infectious disease epidemics. We discuss the SIR model, the renewal...
Monday 30 December 2019 : Does a given bacterial gene live on a plasmid or the chromosome? What other genes live on the same plasmid? In this episode, we hear from...
Friday 29 November 2019 : In this episode, Benjamin Callahan talks about some of the issues faced by microbiologists when conducting amplicon sequencing and...
Tuesday 22 October 2019 : In this episode, Luke Anderson-Trocmé talks about his findings from the 1000 Genomes Project. Namely, the early sequenced genomes sometimes...
Friday 27 September 2019 : In this episode, I talk with Irineo Cabreros about causality. We discuss why causality matters, what does and does not imply causality, and...
Friday 30 August 2019 : In this episode, we hear from Romain Lopez and Gabriel Misrachi about scVI—Single-cell Variational Inference. scVI is a probabilistic...
Friday 26 July 2019 : Even though the double-stranded DNA has the famous regular helical shape, there are small variations in the geometry of the helix depending...
Saturday 29 June 2019 : 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...
Friday 31 May 2019 : Modern genome assembly projects are often based on long reads in an attempt to bridge longer repeats. However, due to the higher error rate...
Monday 29 April 2019 : In this episode, we hear from Jacob Schreiber about his algorithm, Avocado. Avocado uses deep tensor factorization to break a...
the bioinformatics chat
Roman Cheplyaka
#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...
#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...
#54 Seeding methods for read alignment with Markus Schmidt
In this episode, Markus Schmidt explains how seeding in read alignment works. We define and compare k-mers, minimizers, MEMs, SMEMs, and...
#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...
#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...
#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...
#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...
#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...
#48 Machine learning for drug development with Marinka Zitnik
In this episode, Jacob Schreiber interviews Marinka Zitnik about applications of machine learning to drug development. They begin their...
#47 Reproducible pipelines and NGLess with Luis Pedro Coelho
NGLess is a programming language specifically targeted at next generation sequencing (NGS) data processing. In this episode we chat with its...
#46 HiFi reads and HiCanu with Sergey Nurk and Sergey Koren
In this episode, I continue to talk (but mostly listen) to Sergey Koren and Sergey Nurk. If you missed the previous episode, you should...
#45 Genome assembly and Canu with Sergey Koren and Sergey Nurk
In this episode, Sergey Nurk and Sergey Koren from the NIH share their thoughts on genome assembly. The two Sergeys tell the stories behind...
#44 DNA tagging and Porcupine with Kathryn Doroschak
Porcupine is a molecular tagging system—a way to tag physical objects with pieces of DNA called molecular bits, or molbits for...
#43 Generalized PCA for single-cell data with William Townes
Will Townes proposes a new, simpler way to analyze scRNA-seq data with unique molecular identifiers (UMIs). Observing that such data is not...
#42 Spectrum-preserving string sets and simplitigs with Amatur Rahman and Karel Břinda
In this episode, we hear from Amatur Rahman and Karel Břinda, who independently of one another released preprints on the same concept,...
#41 Epidemic models with Kris Parag
Kris Parag is here to teach us about the mathematical modeling of infectious disease epidemics. We discuss the SIR model, the renewal...
#40 Plasmid classification and binning with Sergio Arredondo-Alonso and Anita Schürch
Does a given bacterial gene live on a plasmid or the chromosome? What other genes live on the same plasmid? In this episode, we hear from...
#39 Amplicon sequence variants and bias with Benjamin Callahan
In this episode, Benjamin Callahan talks about some of the issues faced by microbiologists when conducting amplicon sequencing and...
#38 Issues in legacy genomes with Luke Anderson-Trocmé
In this episode, Luke Anderson-Trocmé talks about his findings from the 1000 Genomes Project. Namely, the early sequenced genomes sometimes...
#37 Causality and potential outcomes with Irineo Cabreros
In this episode, I talk with Irineo Cabreros about causality. We discuss why causality matters, what does and does not imply causality, and...
#36 scVI with Romain Lopez and Gabriel Misrachi
In this episode, we hear from Romain Lopez and Gabriel Misrachi about scVI—Single-cell Variational Inference. scVI is a probabilistic...
#35 The role of the DNA shape in transcription factor binding with Hassan Samee
Even though the double-stranded DNA has the famous regular helical shape, there are small variations in the geometry of the helix depending...
#34 Power laws and T-cell receptors with Kristina Grigaityte
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...
#33 Genome assembly from long reads and Flye with Mikhail Kolmogorov
Modern genome assembly projects are often based on long reads in an attempt to bridge longer repeats. However, due to the higher error rate...
#32 Deep tensor factorization and a pitfall for machine learning methods with Jacob Schreiber
In this episode, we hear from Jacob Schreiber about his algorithm, Avocado. Avocado uses deep tensor factorization to break a...
