anvi’o empowers its users to navigate through ‘omics data without imposing rigid workflows.

users still needing considerable expertise to interpret the results.

inter-dependencies of the data types and the various data formats that need to ‘talk’ to each other.

Assembly graphs produced by different tools from the same data may differ significantly, posing a challenge to tools for downstream processing tasks

routine clinical adoption of WGS is hindered by factors such as high costs, technical complexity, and the requirement for bioinformatics expertise for data analysis

user-friendly web-based platform Pathogenwatch, which facilitates species identification, molecular typing, and antimicrobial resistance (AMR) prediction

K-mer-based tools such as Kraken2 [14], KrakenUniq [15], Bracken [16], Centrifuge [17], CLARK/CLARKS [18, 19], Ganon [20, 21], Taxor [22], and Sylph [23] are known for their speed and scalability to large databases, but often trade precision for speed

AI can be a powerful tool for helping scientists dig into results and more quickly identify interesting patterns

Scientists spend a significant proportion of their time transforming and structuring data for analysis