Tsbrowse: an interactive browser for Ancestral Recombination Graphs
Karthikeyan, S.; Jeffery, B.; Mbuli-Robertson, D.; Kelleher, J.
Show abstract
Ancestral Recombination Graphs (ARGs) represent the interwoven paths of genetic ancestry for a set of recombining sequences. The ability to capture the evolutionary history of samples makes ARGs valuable in a wide range of applications in population and statistical genetics. ARG-based approaches are increasingly becoming a part of genetic data analysis pipelines due to breakthroughs enabling ARG inference at biobank-scale. However, there is a lack of visualisation tools, which are crucial for validating inferences and generating hypotheses. We present tsbrowse, an open-source Python web-app for the interactive visualisation of the fundamental building-blocks of ARGs, i.e., nodes, edges and mutations. We demonstrate the application of tsbrowse to various data sources and scenarios, and highlight its key features of browsability along the genome, user interactivity, and scalability to very large sample sizes. AvailabilityPython package: https://pypi.org/project/tsbrowse/, Development version: https://github.com/tskit.dev/tsbrowse, Documentation: https://tskit.dev/tsbrowse/docs/
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.