frogs_preprocess

frogs_preprocess performs denoising and dereplication of metagenomic sequencing datasets to improve sequence quality for downstream microbial community analyses.

Key Features:

• Denoising: Reduces sequencing noise and erroneous reads in metagenomic datasets to improve downstream analysis accuracy.
• Dereplication: Identifies and removes duplicate sequences to reduce redundancy and computational load.
• Galaxy integration: Executes workflows within the Galaxy framework and communicates via the Galaxy API or the Bioblend library to run analyses on Institut Pasteur storage and compute clusters.

Scientific Applications:

• Metagenomic data preprocessing: Prepares metagenomic datasets for taxonomic, functional, and diversity analyses by improving data quality through denoising and dereplication.
• Environmental microbiome studies: Processes complex environmental microbiome sequencing datasets to enable more reliable community composition and diversity assessments.
• Human-associated microbiome studies: Cleans human-associated microbial sequencing data to support precise analyses of host-associated microbial populations.

Methodology:

Operates within the Galaxy framework and invokes workflows via the Galaxy API or the Bioblend library to execute preprocessing on the Institut Pasteur cluster.