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MGX 2.0: Shotgun- and assembly-based metagenome and metatranscriptome analysis from a single source

Jaenicke, S.; Diedrich, S.; Goesmann, A.

2023-09-23 bioinformatics
10.1101/2023.09.21.558800 bioRxiv
Show abstract

Metagenomics studies have enabled scientists to analyze the genetic information of natural habitats or even complete ecosystems, including otherwise unculturable microbes. The processing of such datasets, however, remains a challenging task requiring extensive computational resources. MGX 2.0 is a versatile solution for the analysis and interpretation of microbial community sequence data. MGX 2.0 supports the processing of raw metagenomes and metatranscriptomes, but also enables assembly-based strategies, including downstream taxonomic binning, bin quality assessment, abundance quantification, and subsequent annotation coming from a single source. Due to the modular design of MGX, users are able to choose from a wide range of different methods for microbial community sequence data analysis, allowing them to directly compare between read-based and assembly-based approaches or to evaluate different strategies to analyze their data.

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The top 7 journals account for 50% of the predicted probability mass.

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"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.