# De Novo Genome Assembly

At branching points in unitig graphs, de novo assembly previously had to choose a continuation from topology, paired-end evidence, or coverage heuristics, while the sequence itself was rarely scored directly. RASTRO scores each candidate extension by bits-per-base surprisal, either from a sample-specific n-gram model or from the pretrained DNA language model Evo2, and checks the choice against boundary k-mers counted in the raw reads. On HIV-1 and SARS-CoV-2 unitig graphs, the sample-adaptive RASTRO-S improved agreement with read-supported choices as context length grew from n=5 to n=10, above random selection and a longest-extension greedy baseline; the abstract and the results table disagree on the HIV-1 value at n=10.

At branching points in unitig graphs, de novo assembly previously had to choose a continuation from topology, paired-end evidence, or coverage heuristics, while the sequence itself was rarely scored directly. RASTRO scores each candidate extension by bits-per-base surprisal, either from a sample-specific n-gram model or from the pretrained DNA language model Evo2, and checks the choice against boundary k-mers counted in the raw reads. On HIV-1 and SARS-CoV-2 unitig graphs, the sample-adaptive RASTRO-S improved agreement with read-supported choices as context length grew from n=5 to n=10, above random selection and a longest-extension greedy baseline; the abstract and the results table disagree on the HIV-1 value at n=10.