Excited to preprint our latest work (w/ Drew DeHaas, Zhibai Jia, Leo Speidel) on using ARGs for demographic inference. w/ applications using data from 1000 Genomes Project. www.biorxiv.org/content/10.1...

Very proud of this manuscript with two talented undergraduate students, Aditya Syam and Chris Adonizio. We are continuing to push towards more scalable statistical genetics with Genotype Representation Graphs, and this is the start. www.biorxiv.org/content/10.1...

Our work (by Drew DeHaas) on an extremely simple yet efficient binary genotype format - designed to facilitate scalable bioinformatics tool development. www.biorxiv.org/content/10.1...

📢In a recent News & Views, @ryanlayer.bsky.social discusses a data structure introduced by @aprilwei.bsky.social and colleagues for reducing storage and computational costs for phased whole-genome polymorphisms. www.nature.com/articles/s43... 🔓https://rdcu.be/d8ay3

Our work w/ two co-first authors Drew DeHaas and Ziqing Pan is now published. GRG allows large amounts of WGS polymorphism data to be analyzed in RAM via graph traversal & algebra operations & has some intrinsic connection w/ popgen data generating process & is different from ARG

We introduced an ARG-inspired data structure, Genotype Representation Graph (GRG), to enable lossless data compression and efficient computation through graph traversal. Developed a fast inference method. Cost ~80 GBP to convert 350TB VCF (200,000 UKBiobank WGS) into 160 GB GRG. t.co/0badfCYz47