Back

Assemblies of long-read metagenomes suffer from diverse errors

Trigodet, F.; Sachdeva, R.; Banfield, J. F.; Eren, A. M.

2025-04-24 bioinformatics
10.1101/2025.04.22.649783 bioRxiv
Show abstract

Genomes from metagenomes have revolutionised our understanding of microbial diversity, ecology, and evolution, propelling advances in basic science, biomedicine, and biotechnology. Assembly algorithms that take advantage of increasingly available long-read sequencing technologies bring the recovery of complete genomes directly from metagenomes within reach. However, assessing the accuracy of the assembled long reads, especially from complex environments that often include poorly studied organisms, poses remarkable challenges. Here we show that erroneous reporting is pervasive among long-read assemblers and can take many forms, including multi-domain chimeras, prematurely circularized sequences, haplotyping errors, excessive repeats, and phantom sequences. Our study highlights the need for rigorous evaluation of the algorithms while they are in development, and options for users who may opt for more accurate reads than shorter runtimes.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

50% of probability mass above

"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.