Genomics – Joseph Guhlin: Bioinformatics and Genomics

Machine Learning for Variant calling with DeepVariant from Google Brain

Last December Google Brain released DeepVariant, a machine-learning based variant caller using convolutional neural networks. While PacBio and Nanopore (long-read) sequencing become more mainstream, there exist massive amounts of data from 2nd generation sequencing* for populations which still have lots of use. For the Medicago HapMap project, we have 262 accessions with various depth of… Read More »

Select and resequence manuscript published

Select and resequence reveals relative fitness of bacteria in symbiotic and free-living environments. Abstract Assays to accurately estimate relative fitness of bacteria growing in multistrain communities can advance our understanding of how selection shapes diversity within a lineage. Here, we present a variant of the “evolve and resequence” approach both to estimate relative fitness and… Read More »