MetaCompass: Reference-guided Assembly of Metagenomes

no code implementations • 3 Mar 2024 • Tu Luan, Victoria Cepeda, Bo Liu, Zac Bowen, Ujjwal Ayyangar, Mathieu Almeida, Christopher M. Hill, Sergey Koren, Todd J. Treangen, Adam Porter, Mihai Pop

Metagenomic studies have primarily relied on de novo assembly for reconstructing genes and genomes from microbial mixtures.

GraSSRep: Graph-Based Self-Supervised Learning for Repeat Detection in Metagenomic Assembly

1 code implementation • 14 Feb 2024 • Ali Azizpour, Advait Balaji, Todd J. Treangen, Santiago Segarra

Additionally, our experiments with synthetic metagenomic datasets reveal that incorporating the graph structure and the GNN enhances our detection performance.

Node Classification Self-Supervised Learning

Accelerating SARS-CoV-2 low frequency variant calling on ultra deep sequencing datasets

1 code implementation • 7 May 2021 • Bryce Kille, Yunxi Liu, Nicolae Sapoval, Michael Nute, Lawrence Rauchwerger, Nancy Amato, Todd J. Treangen

With recent advances in sequencing technology it has become affordable and practical to sequence genomes to very high depth-of-coverage, allowing researchers to discover low-frequency variants in the genome.